Evaluation of Programmes for Information Industry September 30, 1999
Self-assessment
Computer Science Programme
Contact person:
Dr. Greger Lindén
Email: Greger.Linden@cs.helsinki.fi
Tel. 09-708 44164
Department of Computer Science
P.O. Box 26 (Teollisuuskatu 23)
FIN-00014 University of Helsinki
Tel. 09-708 51
Fax. 09-708 44441
URL: http://www.cs.helsinki.fi
A. Description: Quantitative and qualitative information 2
A.1 Curriculum 1998-99 17
A.2 Research and development projects since 1.1.1998 27
B. Self-assessment: The evaluation of the quality of the programme (faculty) 33
C. Self-assessment: The evaluation of the quality of the programme (students) 39
A. DESCRIPTION: QUANTITATIVE AND QUALITATIVE INFORMATION
The Department of Computer Science was founded in 1967 when the first full professorship in computer science was established at the University of Helsinki. The department belongs to the Faculty of Science along with the Departments of Mathematics, Physics, Chemistry and others, but it is located at Teollisuuskatu 23, in Vallila, Helsinki, in isolation from the others. The department is the largest computer science department in Finland. The department has a single programme, the Computer Science Programme, which is further divided into three sub-programmes: Computer Science, Applied Computer Science and Teacher in Computer Science.
The aim of the programme is twofold. Firstly, the programme strives to provide a modern and all-round advanced level education of computer experts for the needs of the industry sector. Secondly, the department seeks to be among the top-most research institutes within selected research areas of computer science.
The education at the department has been both theoretical and practical, focusing on software design and engineering. Co-operation with the rest of the university and with the industry sector is also of great significance. About half of all master’s theses and advanced level project work is performed either on site in companies or in close co-operation with the industry sector and other departments of the university.
In research, co-operation with various industrial partners is significant. In 1998, the department co-operated with 41 different companies within different research projects. In addition, the department works closely with several other departments at the university.
The department receives basic funding from the university. The Ministry of Education grants additional funding for education through different strategy programmes. The main organisations providing research funding are the Academy of Finland, the National Technology Agency (TEKES) together with the industry sector, and the European Commission. Table 1 summarises the funding received and granted for the years 1998 and 1999.
Table 1: Funding of the Computer Science Programme
|
Funding (thousand marks) |
1998 |
1999 |
|
granted |
||
|
Basic funding |
11 600 |
11 400 |
|
Additional funding for education |
4 800 |
7 200 |
|
- National Information Society Strategy |
2 500 |
2 100 |
|
- Upgrading studies in computer science |
- |
900 |
|
- Increasing education in the Information Industry fields |
- |
1 200 |
|
- Graduate Schools |
2 300 |
2 500 |
|
- Other |
- |
500 |
|
Research funding |
8 500 |
10 400 |
|
- Academy of Finland |
1 700 |
1 700 |
|
- National Technology Agency and Industry |
5 100 |
6 600 |
|
- European Commission |
1 400 |
2 100 |
|
- Other |
300 |
- |
|
TOTAL FUNDING |
24 900 |
29 000 |
The degree programme has undergone a major change between academic years 1998-1999 and 1999-2000. Two new specialisation areas have been introduced and many courses have been split into smaller components. In the following, we present the new degree programme. For comparison, the old degree programme can be found in Appendix A.1.
The degree programme in computer science consists of at least 160 credit units (Master of Science) or 120 credit units (Bachelor of Science). The programme offers three subprogrammes:
- Computer Science,
- Applied Computer Science, and
- Teacher in Computer Science.
Computer Science, which is the area largest in volume and which focuses both on practical and theoretical studies, is further divided into five specialisation areas:
- Algorithms,
- Intelligent Systems,
- Software Engineering,
- Distributed Systems and Data Communication, and
- Information Systems.
The requirements of the bachelor’s and the master’s degrees are as follows.
Bachelor of Science (120 cu)
- Cum Laude Approbatur in Computer Science (at least 55 cu) and maturity test
- Two or more minor subjects (at least 45 cu)
- Other studies (at least 6 cu)
A student studying to be a teacher can complete the bachelor’s degree but s/he will not have competence as a teacher (a master's degree is required).
Master of Science (160 cu)
Computer Science:
- Laudatur in Computer Science (at least 95 cu) and maturity test
- Two or more minor subjects (at least 45 cu)
- Other studies (at least 6 cu)
Applied Computer Science:
- Laudatur in Computer Science (at least 80 cu) and maturity test
- Two or more minor subjects (at least 60 cu)
- Other studies (at least 6 cu)
Teacher in Computer Science:
- Laudatur in Computer Science (at least 75 cu) and maturity test
- Minor subjects (at least 70 cu) including pedagogical studies of 35 cu
- Other studies (at least 6 cu)
Major subject studies
Major subject studies are divided into two levels, Cum Laude Approbatur (46-69 credit units) and Laudatur (depending on subprogramme at least 95, 80 or 75 credit units). Students majoring in computer science start with the Cum Laude Approbatur level. The studies consist of compulsory courses in practical and theoretical computer science as well as project work. The purpose of the Cum Laude Approbatur studies is to provide thorough knowledge in central areas of computer science.
The students then continue with studies on the Laudatur level completing additional courses in computer science. The Laudatur studies also contain seminars and the M.Sc. thesis. The volume of the thesis (16 cu or 10 cu) is about one third of the Laudatur studies. The Computer Science subprogramme divides into five specialisation areas (see above). Applied Computer Science and Teacher in Computer Science have no specialisation areas. Students choose a certain subprogramme (specialisation area) by completing courses in that area, but the division is not always strict, and students may later change to another subprogramme.
Minor subjects and other studies
Students in the Computer Science subprogramme are required to take at least 15 credit units of mathematics. They are, however, free to choose their other minor subjects. Students majoring in Applied Computer Science must take at least two different minor subjects and students in Teacher in Computer Science are required to take at least 35 credit units in a minor subject and 35 credit units of pedagogical studies.
Other studies consist of compulsory language studies, tutoring, introductory presentations of computer science, and optional studies.
Successfully completed studies of at least 160 cu lead to a master's degree in Science (120 cu for a bachelor’s degree).
Postgraduate studies
The postgraduate degrees are the licentiate and the doctorate. The requirements for a licentiate degree are
- a master's degree in computer science,
- an additional 40 credit units of computer science and minor subjects, and
- a licentiate thesis.
Students with a master’s degree in mathematics or physics and Laudatur in computer science may also pursue a licentiate degree.
The requirements for a doctoral degree are the same as for a licentiate degree, but instead of a licentiate thesis a doctoral thesis is required. The doctoral thesis must be defended in a public dissertation and approved of by the Faculty of Science. Many postgraduate students start by taking a licentiate degree and then extend their licentiate thesis into a doctoral thesis.
Postgraduate studies are pursued in two graduate schools, the Helsinki Graduate School in Computer Science and Engineering (HeCSE) and the Graduate School in Computational Biology, Bioinformatics, and Biometry (ComBi). Postgraduate studies are also carried on outside the graduate schools.
Minors in computer science
Students minoring in computer science start by taking courses on the Approbatur level (15-34 credit units). The purpose of the Approbatur level studies is to introduce the student to computers, programming and software design. Approbatur studies include the same courses as students majoring in computer science take at the beginning of the cum laude level. Approbatur studies in computer science are required or optional in some other degree programmes. Minor students can then go on to take courses on the Cum Laude Approbatur level (35-69 cu) and the Laudatur level (at least 70 cu). All students at the university are allowed to take at least 25 cu of computer science. Minor students who wish to take more computer science must have completed their computer science studies with good grades (2/3).
Major changes and improvements
The degree programme in computer science has undergone a major reform between academic years 1998-99 and 1999-2000. Within the Computer Science subprogramme, two new specialisation areas have been introduced. The former General specialisation area has been split into Algorithms and Intelligent systems, and the Software specialisation area has been split into Software Engineering and Distributed Systems and Data Communication. Further, students majoring in computer science now start their computer science studies on the Cum Laude Approbatur level (earlier on the Approbatur level). Many courses in computer science have been divided into smaller parts. The requirements of mathematics (in Computer Science) have been decreased from 26 to 15 credit units.
Other major changes during recent years include the establishment of tutoring (tutoring by teachers) and a programme for prospective researchers ("honours students", see Chapter 5: Teaching and Learning).
The curriculum of the academic year 1998-99 and course descriptions are given in Appendix A.1.
The Laudatur studies are fairly closely connected with the research at the department. Research is pursued within the same areas as the specialisation areas. For each specialisation, there is a research group in charge of a set of Laudatur courses within that area. Many graduate students also participate in research and development projects.
A description of research and development projects is given in Appendix A.2.
The department has a full-time staff of 45 teachers, 15 administrative persons, and 57 researchers, altogether 116 persons (1st January 1999, see Table 2). In addition, the department employs 30-50 part-time teachers yearly. Many of the part-time teachers are graduate or postgraduate students. Due to saving requirements and a high demand of computer scientists in the IT sector, an additional 17 positions were vacant in the beginning of the year.
Many teachers and researchers are former students of the department. Some have experience from industry and commerce. Prof. Jukka Paakki forms a special link to the industry sector, working part-time at the department and part-time at the Nokia Research Centre. Occasionally, teachers from the industry sector and other universities are invited to give courses or lectures at the department. An important form of co-operation with the industry sector is that about half of the master’s theses and project works are performed outside the department.
Table 2: Full-time staff of the Department
|
Positions |
Basic funding |
Additional funding |
Research funding |
Total |
Vacant |
Total in position |
S |
|
Professors |
9 ½ |
1 ½ |
1 |
12 |
1 |
11 |
ü |
|
Lecturers |
13 ½ |
13 ½ |
1 |
12 ½ |
÷ |
||
|
Senior Assistants |
6 |
3 |
9 |
5 |
4 |
ý 44 ½ |
|
|
Assistants |
14 |
2 |
16 |
5 |
11 |
÷ |
|
|
Teachers |
11 |
11 |
4 |
7 |
þ |
||
|
Administrative |
13 |
2 |
1 |
16 |
1 |
15 |
15 |
|
Researchers |
2 |
18 |
20 |
20 |
ü |
||
|
Research Assistants |
2 |
19 |
21 |
21 |
ý 57 |
||
|
Postgraduate students |
16 |
16 |
16 |
þ |
|||
|
Total |
67 |
28 ½ |
39 |
134 ½ |
17 |
117 ½ |
117 ½ |
In the past, positions at the university have to some degree been divided into researchers and teachers. New regulations at the university require employees to work 1,600 hours per year. The department can rather freely assign tasks among the employees. This means that the work of a teacher can more easily be divided into teaching and research periods.
There is no explicit faculty development programme but the department gives advice to new teachers in their work. Some informal meetings between the teachers are arranged and occasionally the department has arranged further education of the staff (such as in scientific writing). The students also give feedback of the instruction twice per term. In autumn 1998, a working group consisting of teachers and students has made a proposal for recruiting new teachers and enhancing pedagogical skills among older teachers.
The teachers are encouraged by several incentives. In 1997 Jaakko Kurhila received the Educational Technology Award by the university for the best project plan for an educational application (Agents in Special Needs Education, FIM 50,000). In 1998 Lecturer Arto Wikla received the same award for the best educational application in use (Introduction to Programming, a four-credit-unit course on the World Wide Web, FIM 25,000). An incentive for teachers to achieve higher academic degrees is the prospect of a rise in salary. Also, the teaching duties of teachers, who are working on their Ph.D. Thesis, are usually smaller than for other teachers.
The programme accepted 270 new students in 1998 and 310 new students in 1999. The basic admission limit is 180 new students per year. The programme has received additional funding for accepting new students through information strategy programmes (60+30 new students in 1999) and through a programme for upgrading studies (40 students in 1999). In September 1999 there were 1950 students enrolled with computer science as their major subject (1793 in 1998). Additionally, there are about 800 students minoring in computer science.
The student profiles are fairly uniform. Most of the new students have completed their high school matriculation degree. Admission is based either on the matriculation certificate or on an entrance test, or both. In some cases, students are also accepted based on other degrees; in 1998 three students were accepted based on vocational degrees. Annually some 20-25 students are accepted based on studies in other universities. Also annually, some 15-20 mathematics or physics students change (by application) their major subject to computer science.
In 1999, 40 students were accepted for upgrading their studies in computer science. They usually have a degree in another subject and some computer science studies. Their goal is to achieve a master’s degree in computer science in two years.
Employment in the IT field has been very good during recent years. The most recent statistical figures date from 1996. According to a study by the Finnish Statistical Office concerning the year 1996 and students who graduated in the time period 1987-1996, very few graduated students were unemployed. Altogether, 373 students graduated from the Computer Science Programme during 1987-1996. About 10% of the graduates have moved abroad, died or completed a higher or similar degree. Out of the remaining 342 graduates, 326 (95.3 %) were employed, 4 (1.2 %) unemployed, 3 (0.9 %) were still studying, and 9 (2.6 %) categorised as others (recruits, pensioners, or persons doing household work). Table 3 shows the corresponding figures for the licentiate and doctoral degrees. It also lists the figures for all graduated students in the Faculty of Science and in the University of Helsinki, and for comparison, the figures for graduates of all faculties of science in Finnish universities, for graduates of all Finnish technical universities and for graduates of all Finnish universities.
Table 3: Employment in 1996 of students who graduated in 1987-1996
|
Degree |
Graduated |
Employed |
Unemployed |
Student |
Other |
|
M.Sc./Computer Science |
342 / 373 |
95.3 % |
1.2 % |
0.9 % |
2.6 % |
|
Ph.L./Computer Science |
13 / 22 |
92.3 % |
0 % |
7.7 % |
0 % |
|
Ph.D./Computer Science |
15 / 15 |
100.0 % |
0 % |
0 % |
0 % |
|
M.Sc./Faculty of Science/Univ. Hels. |
3 284 / 4 079 |
80.9 % |
6.0 % |
7.6 % |
5.5 % |
|
M.Sc. & M.A./University of Helsinki |
235 75 / 27 125 |
83.9 % |
5.3 % |
6.0 % |
4.9 % |
|
M.Sc./Finnish faculties of science |
10450 / 12 697 |
81.0 % |
7.0 % |
7.0 % |
5.0 % |
|
M.Sc./Finnish technical universities |
16 037 / 17 840 |
89.0 % |
4.0 % |
3.0 % |
4.0 % |
|
M.Sc. & M.A./All Finnish universities |
104 140 / 117 325 |
85.0 % |
5.5 % |
5.1 % |
4.5 % |
Most of the students are employed by IT companies and other industries during their second or third study year. This slows down their study progress and in many cases students never graduate. The reason lies in the high need of computer experts in the IT field. Many students also change programmes after their first or second year (e.g. to the Helsinki University of Technology or the Faculty of Medicine). About 85% of the first year students are enrolled at the Department after one year and 70% after two years. Many choose to remain enrolled at the university without studying. In general, a third of the first year students complete their master’s degree. In 1998, 48 students completed their master’s degree; these students completed their degree in an average time of 7.3 years.
The department has appointed an alumni contact person in March 1999. Co-operation with alumni has until now mainly been based on personal acquaintance between teachers and alumni.
Teaching is performed in several different ways. Computer science lecture courses are given either during a six-week period (2-3 credit units) or one term (12-13 weeks, 4-5 credit units). A typical course consists of 2-4 lectures/week (a lecture lasts 45 minutes) and of about 2 hours/week of problem solving, discussion and repetition sessions in small groups of about 10 to 20 students. In some courses, the students are required to write essays or implement small computer programs.
In the computer laboratories, students design and implement solutions to selected algorithmic problems. The laboratories are supervised in small groups of 6 to 12 students. On the undergraduate level, students work independently (or sometimes in pairs). On the graduate level, students take a course in software engineering and obtain practical skills in a medium-sized (6 credit unit) software engineering project.
Students also attend seminar courses enrolling 5 to 15 students. In these seminars the students read current scientific literature, write surveys, and give oral presentations. A seminar group normally meets 2 hours per week yielding 2 credit units per term.
Attendance is compulsory only in some exercise sessions on the undergraduate level and in seminars. In spite of this, many students choose to attend lectures and the participation in exercise sessions is encouraged, e.g. with extra points if the students have solved given problems on their own.
Students are encouraged to give (anonymous) feedback twice per term. The programme maintains a course evaluation system where students are able to comment on teaching, facilities, etc.
Learning resources include textbooks, and compendiums and teaching aids developed by teachers at the department. On the graduate level most of the literature is in English. Computers are used not only for computer laboratory work, but also for writing essays or for information retrieval (e.g. through WWW). The students use the library both in their seminar work and on other graduate courses. All course books are also found in the library.
On the undergraduate level, students achieve basic skills in solving algorithmic or data-oriented problems. The students learn how to use the technical and scientific literature in finding solutions to these problems. On the graduate level, students concentrate on some specialised area within computer science. Their aim is to achieve expert knowledge in this area and focus is on both practical and theoretical skills. This basis is essential for postgraduate students.
Presentation and communication skills as well as teamwork are given some attention. The students give oral presentations in seminars. They also learn how to present solutions to different problems in the exercise sessions of the courses and in poster sessions in some courses. The software engineering project teaches both management and communication skills. The students form groups of 5-6 persons, where they elect their own chairperson(s) and delegate responsibilities in the project to different members.
Writing skills are taught in a course on scientific writing. The students also produce documentation of their computer laboratory work. Their writing skills are finally tested in their thesis work and in a maturity test. Language skills are taught in several ways. About one fifth of the students write their master’s thesis in English (9 out of 48 in 1998), the rest writes the thesis in Finnish or Swedish. Language studies in the other domestic language (Swedish or Finnish) and in a foreign language are also required in the curriculum (altogether 3-4 credit units). Some courses and seminars are also given in English.
Students are encouraged to work in industries during the summers to enhance their practical skills. Many students also work as part time teachers or as research assistants at the department.
Recent innovations include tutoring (tutoring by teachers) and a programme for prospective researchers. The aim of the tutoring is to make the students better acquainted with the department and the faculty. The students are divided into small groups during their second study year. In each group, a teacher guides and supervises the students and their study plans. The group organises small seminars on developing working skills with the computer, on the specialisation areas and on other general things regarding academic and working life.
Students in the researcher programme aim at a postgraduate degree, completing the master's degree as an intermediate goal. The students follow the same syllabus as other students, but they are recommended to complete more courses in mathematics than is required. As graduate students they are employed in research projects and enrolled in one of the graduate schools. Students are enrolled as prospective researchers based on applications. The programme started in 1998 by accepting 15 prospective researchers.
In some courses, the students write learning diaries where they note what and how they learn in the course. The diaries are taken into consideration in the assessment of the course.
Assessment methods include written and oral exams (courses), assessment based on written work (theses, essays/surveys, documentation) and laboratory work (programming, program design), and assessment based on oral and written presentations and participation (seminars).
Written exams may include essay questions or applied problems, such as programming problems or other computing problems. Written work is assessed on both content and language. Laboratory work is assessed on functionality and innovative ideas as well as documentation. Seminars are assessed on a written survey, an oral presentation of the survey and participation activity in the seminar. Students may also assess each other as opponents. Some courses are also partly assessed based on learning diaries and participation in exercise sessions.
Criteria for the assessment are defined course-wise, but most courses follow the same criteria. Each assessment method of the course is worth a certain amount of points. Usually, to pass a course the student is required to have obtained at least half of the maximum score. Points can be achieved in exams, laboratory work, essays, etc., and they may also be based on how many exercises the student has been able to solve during exercise sessions. Usually, exam points dominate (60-90%).
Each course is examined individually with grades: 3/3 = excellent, 2 = good, 1 = satisfactory. Study components, such as the Cum Laude Approbatur or the Laudatur, are graded based on mean grades of the component courses.
Results of exams as well as assignments and their solutions are published at the department and on the web. The students may get to know the details of their exam assessment at the teachers’ reception hours. If the students disagree, they may file an official complaint to the university.
The main source for student guidance is the Faculty Programme Book by the Faculty of Science. It is published annually and contains general information about the department (contact information, teachers, etc.) as well as examination requirements and a suggestion for how to complete the master’s degree in five years. It also contains the curricula including short course descriptions, a presentation of the specialisation areas as well as postgraduate studies and graduate schools. Other guides contain information on social financial support, health care and language studies.
The WWW pages of the department are another important source for information. They include the faculty programme book in electronic form as well as course descriptions, schedules for courses and exercise sessions, and in many cases lecture notes of the courses. They also include information about the faculty and research at the department as well as information about the library and the computing facilities. Some courses have set up news groups for discussing problems related to the course. The course descriptions and schedules are also available on the departmental bulletin boards.
The teachers introduce the department to new students each year in the beginning of the autumn term. Older students tutor first year students (peer tutoring). Second year students are obliged to participate in tutoring groups lead by teachers ("teacher tutoring", see Section 5 on Teaching and Learning). There are five student advisors at the department including a foreign student advisor and advisors on all programme levels (Approbatur, Cum Laude Approbatur, Laudatur). All teachers have regular office hours weekly for consultation during term-time. The Study Office at the Faculty of Science helps students with applications and degree certificates, and the Information and Counselling Office of the university provides general inquiry services.
Each year there is a seminar presenting the specialisation areas of the programme. Occasionally, colloquiums are organised for presenting both departmental research and innovations in industry. In April 1999, the department organised for the fifth year in a row, an Open Doors Day with presentations of research and curriculum to the students and the industries.
Student progression is monitored in different ways. The university intends to introduce (from 1999) a requirement for students to take at least 10 credit units per year. Students who do not succeed will be invited to make a personal study plan. The student financial aid system requires students to take at least 20 credit units per year.
Students who have taken at least 100 cu receive departmental information about their graduate studies, especially their master’s thesis. They are informed about different possibilities about choosing supervisors and thesis subjects.
Library
The department maintains a library with large collections of literature on computer science. The library is jointly financed with the University IT Department and is mainly used by the staff and advanced students of the department.
The library now holds about 52,000 volumes of literature, making it the largest computer science library in Finland. The annual cumulative is about 1,200 monographic titles and 300 journal subscriptions. Course books are available for reading on the premises. The floor area is 408 sq. meters including a reading room of 60 seats. Admission to the premises is free and the collections are freely available to all visitors. Home loans, however, are normally granted only to university personnel and advanced students of the department.
To help users search and locate the required literature, the library maintains a www-database of its holdings. The database includes all journal titles and about 41,000 monographic titles, classified according to the CR Classification System of the ACM. The library is also responsible for the distribution of departmental reports, including Ph.D. theses. Paper copies may be requested from the library, and electronic versions are accessible through the department's FTP server.
The library has two full-time employees, one librarian and one secretary, assisted in their work by a part-time bookbinder and a library committee consisting of several members of the faculty.
Computing Facilities
The department offers a wide range of services to support the computing activities of the academic staff and students. The policy is to provide access to advanced hardware and software systems.
The computing facilities include a farm of servers (general-purpose computers, file servers, and dedicated servers for mail, WWW, FTP etc.) and a network of workstations and PC microcomputers. The departmental general-purpose computers include a Sun UltraSPARC Enterprise 450 server and an Alpha based Citum Power System (a repackaged Aspen server). The main file servers are Intel Pentium based systems running Linux and utilising RAID technology. The total disk space is currently well over 200 Gbytes. The Alpha and Intel Pentium based machines use Linux, but the SPARC computers run SunOS/Solaris. Together these systems support a wide variety of services, languages and software tools including electronic mail and news, graphics and visualisation tools, several typesetting systems, and relational database systems. Special attention has been paid to security and reliability.
The workstation network consists of about 310 PCs (mostly Pentium (MMX/II/III) with high-resolution monitors) running Linux. Windows 95, Windows 98 or Windows NT can be used as an alternative for Linux. About 40 of the Linux workstations are mobile laptops which can join and leave the network dynamically. Networking is based almost entirely on switched 100 Mbit/s Ethernet with an optical backbone. The mobile laptops can also utilise a departmental 2 Mbit/s radio network that currently has 9 base stations. On the UNIX side (Linux, SunOS/Solaris) NFS is used to share common resources. On the Windows side Samba (a UNIX hosted LAN Manager Server) is used. The workstations are used as tools for software development, in research and all levels of teaching.
The network of the department is connected through a firewall to the university backbone network, giving access to computers at the University IT Department as well as to the FUNET wide area network that links Finnish universities and research establishments. The computers operated by the IT Department include SPARC (Sun, Axil), Compaq Alpha and HP machines running under UNIX. Services provided by the IT Department include Oracle and Ingres database management systems, the SAS statistical analysis package, the NAG numerical library, and Pascal, Ada, and Prolog programming environments.
In addition, the department has access to a Cray C94, a Cray T3E, an SGI Origin 2000, a Compaq AlphaServer SG140, and other supercomputers at the Center for Scientific Computing.
The national FUNET network is further connected to the Nordic University Network, Nordunet, with a 155 Mbit/s connection. The Nordunet has a 310 Mbit/s connection capacity to the United States as well as many 155 Mbit/s connections to the European network infrastructure. This means that the department is very well connected to the Internet.
Other educational facilities are available as follows. Students have direct access to about 100 PCs in 9 computer rooms. The IT Department of the university, situated in the same building as the department, gives access to an additional 48 PCs and terminals in 5 computer rooms. All members of the faculty also have their own PC. There are 6 small and 12 medium-sized classrooms at the department as well as 3 bigger lecture halls including an auditorium seating 250. Many of the classrooms are equipped with a computer. Some also include a video projector. There are also wireless computer sets including projectors that can be used in any classroom.
Both students and personnel have their own recreation rooms for informal meetings, coffee, etc. In the building, there is also a student cafeteria.
In the autumn of 1999, the department is extending its facilities. Three new computer rooms with about 60 PCs will be included as well as a medium-sized classroom and additional offices for the personnel.
The department co-operates with national and international institutions in both education and research.
The system of flexible study opportunities is based on a co-operation agreement among the institutions of higher education mainly in the Helsinki area. (In Finnish, this is called the JOO-arrangement.) Students may put together a degree that best suits them by taking courses in one of the participating universities in subjects not available at their own university. Some restrictions have, however, been made due to a lack of resources.
Thesis work is performed to a large extent outside the department in industries or commercial undertakings, or on the request from outside. About 40% of the master’s theses and 50% of the software engineering projects were performed outside the department in 1998.
From 1999, the department will co-operate with six high schools in the Helsinki area. About 25 high school students are accepted to study some computer science courses (with screening based on a special entrance exam). They may substitute school courses with courses in computer science at the department. If the students later decide to continue their studies at the department, computer science courses completed during school time will become part of their degree.
The department participates in the Erasmus and Socrates exchange student programmes of the European Union as well as the Nordic NORDplus programme. Seven foreign exchange students studied at the department, while eight students from the department studied abroad in 1998. In the same year, there were 26 foreign students majoring in computer science at the university and 57 foreign students taking classes in computer science (both majors and minors).
Postgraduate studies are pursued in two graduate schools, the Helsinki Graduate School in Computer Science and Engineering (HeCSE), and the Graduate School in Computational Biology, Bioinformatics, and Biometry (ComBi). HeCSE is in co-operation with the Helsinki University of Technology; ComBi in co-operation with the Universities of Tampere and Turku. Postgraduate studies are also pursued outside the graduate schools.
A new research institute, the Helsinki Institute of Information Technology (HIIT) has been founded in 1999 as a joint venture between the University of Helsinki and the Helsinki University of Technology. Its main goal is to provide facilities as well as funding for top researchers in computer science and engineering. The institute will co-operate with both national and foreign institutions.
The department collaborates with the University of Tampere in three co-funded research projects. Other research co-operation partners are, among others, the Universities of Joensuu, Jyväskylä, Kuopio and Turku as well as other departments of the University of Helsinki. The department also collaborates with several foreign universities and companies within research and development projects funded by the European Commission.
The Finnish Academy, the National Technology Agency and the European Commission are the main providers of research funding of the department. Many research projects are co-funded by the industries. In 1998, 41 different industrial partners co-funded projects of the department. One of the professorships at the department is shared between the department and the Nokia Research Centre. The professor works half-time at the department, and half-time at Nokia enhancing co-operation between the department and the industry sector.
The department participates in several international research networks, among others the EC funded Neural Computational Learning Network (NeuroCOLT), the Network of Excellence in Machine Learning (MLnet), and the Network of Excellence for Agent-Based Computing (AgentLink).
In 1998, 16 foreign researchers and teachers visited the department; 6 of them stayed for one term or more. In 1998, a total of 42 teachers and researchers of the department visited universities or research institutions abroad or took part in international conferences. In addition, 8 researchers from the department stayed at foreign institutions for a longer time.
The department has been active as a conference organiser as well. In 1997, the department organised the Sixth Scandinavian Conference on Artificial Intelligence (SCAI ’97, an international conference with about 80 participants), and in June and July 1999 it organised the Second IFIP WG 6.1 International Working Conference on Distributed Applications and Interoperable Systems (DAIS). The department will organise the 5th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE) in the year 2000.
The new course schedule for the next study year is presented to the steering committee of the department for approval every spring. The schedule is published in the Programme Book of the Faculty of Science, on the departmental bulletin boards and in the World Wide Web. The schedule is revised at the beginning of each term by increasing or decreasing the teaching based on student registrations, for example.
The steering committee of the department also instigates changes in the objectives of the programme. The latest changes in the educational requirements have been implemented for the academic year 1999-2000. Other questions concerning objectives and the curriculum are discussed in departmental meetings (at least one per term). The department keeps up-to-date with international trends in computer science education, especially curricula recommendations in North American universities.
The students may give anonymous course feedback twice per term. The results are delivered to the teachers and they are also processed by the steering committee of the department, which recommends that the teachers publish the feedback results (e.g. in WWW).
Each of the specialisation areas has one professor who is responsible for the quality and enhancement of the teaching in that sector. Regular faculty meetings are held within the specialisation areas to discuss programme requirements and course contents. All specialisation areas are closely connected with the research at the department. Teachers are therefore up-to-date with new inventions and innovations within information technology as well as computer science education.
Dr. Greger Lindén was assigned from the beginning to co-ordinate the self-assessment at the department. He has been in charge of writing and collecting the material for the qualitative and quantitative description (Part A) and the self-assessment done by the faculty (Part B). Several professors and other staff members have commented and corrected the assessment report, which has been several times presented in the steering committee meetings of the department and which has also been available on the web (all draft versions) for the personnel to read and comment on.
The students were asked in an early stage to comment on the qualitative and quantitative description of the department, and to give their own independent self-assessment report (Part C). The student report has not been processed or modified by the department (safe some language corrections).
Work plan for the self-assessment 1999
|
February-March |
Dr. Greger Lindén and Profs. Esko Ukkonen and Hannu Erkiö and Amanuensis Teija Kujala prepare the answer to the survey of the evaluation of the information technology programmes. |
|
19 March, 1999 |
The survey report is returned to the Finnish Higher Education Evaluation Council. |
|
April-May |
Greger Lindén and Prof. Esko Ukkonen prepare the assessment report. The preliminary report is available at all times in WWW for commentaries. |
|
24 May, 1999 |
The preliminary report (first draft) is presented to the steering committee of the department. |
|
24-31 May, 1999 |
Comments by Profs. Ukkonen, Erkiö and Pekka Kilpeläinen are included in the report. |
|
June-September |
Personnel and students are requested to comment on the preliminary report. |
|
September |
The report is finalised and presented to the steering committee of the department on 6 September 1999. |
|
September |
Many comments by Profs. Timo Alanko and Hannu Erkiö. Many other members of the staff give comments and suggest corrections. The students return their answer. Language is checked made by Marina Kurtén. |
|
30 September 1999 |
The report is returned to the Finnish Higher Education Evaluation Council at the latest. |
|
19 October, 1999 |
The evaluation panel visits the department. |
Appendix A.1: Curriculum 1998-99
|
CURRICULUM CONTENT |
Year 1998-99 (credit units) |
|
Compulsory subjects: |
|
|
In mathematics-natural science |
|
|
In basic information technology |
|
|
In basic electronics |
|
|
Major subjects of the programme |
³ 95 |
|
Minor subjects of the programme |
³ 45 |
|
Of the option: Computer Science Line |
|
|
In communication, negotiation and languages |
|
|
In industrial management |
|
|
Optional subjects |
³ 5 |
|
Practical work experience |
|
|
Thesis of studies |
|
|
TOTAL |
³ 160 |
Curriculum requirements 1998-99
BACHELOR OF SCIENCE (120 cu)
- Cum Laude Approbatur in Computer Science (at least 55 cu) and maturity test
- Two or more minor subjects (at least 45 cu)
- Other studies (at least 6 cu)
A student studying to be a teacher can complete the bachelor’s degree but s/he will have competence as a teacher (a master’s degree is required).
MASTER OF SCIENCE (160 cu)
General Computer Science, Software Systems, and Information Systems:
- Laudatur in Computer Science (at least 95 cu)
- Two or more minor subjects (at least 45 cu)
- Other studies (at least 5 cu)
Applied Computer Science:
- Laudatur in Computer Science (at least 80 cu)
- Two or more minor subjects (at least 60 cu)
- Other studies (at least 6 cu)
Teacher in Computer Science:
- Laudatur in Computer Science (at least 75 cu)
- Minor subjects (at least 70 cu) including pedagogical studies (35 cu)
- Other studies (at least 6 cu)
1. Major subject
Approbatur in Computer Science:
|
Introduction to Programming |
4 cu |
|
Computer Systems Organisation |
3 cu |
|
Information Systems |
4 cu |
|
Programming Project |
2 cu |
|
Optional studies |
³ 2 cu |
|
³ 15 cu |
|
|
Cum Laude Approbatur in Computer Science:
|
|
|
Approbatur |
³ 15 cu |
|
Data Structures |
4 cu |
|
Concurrent Systems |
4 cu |
|
Database Systems I |
4 cu |
|
Data Structures Project |
2 cu |
|
Information Systems Project |
2 cu |
|
Scientific Writing |
4 cu |
|
Software Engineering |
4 cu |
|
Software Engineering Laboratory |
6 cu |
|
Theory of Computing |
4 cu |
|
Computer Uses in Education |
4 cu |
|
Optional studies |
³ 6 cu |
|
³ 55 cu |
|
|
Laudatur in Computer Science:
|
|
|
General Computer Science |
|
|
Cum Laude Approbatur |
³ 55 cu |
|
Design and Analysis of Algorithms |
5 cu |
|
Optional courses |
³ 15 cu |
|
Seminars |
³ 4 cu |
|
Master’s thesis |
16 cu |
|
³ 95 cu |
|
|
Software |
|
|
Cum Laude Approbatur |
³ 55 cu |
|
Compilers, or |
5 cu |
|
Distributed Operating Systems |
4 cu |
|
Optional courses |
³ 15-16 cu |
|
Seminars |
³ 4 cu |
|
Master’s thesis |
16 cu |
|
³ 95 cu |
|
|
Information Systems |
|
|
Cum Laude Approbatur |
³ 55 cu |
|
Database Systems II |
5 cu |
|
Optional courses |
³ 15 cu |
|
Seminars |
³ 4 cu |
|
Master’s thesis |
16 cu |
|
³ 95 cu |
|
|
Applied Computer Science |
|
|
Cum Laude Approbatur |
³ 55 cu |
|
Optional Laudatur courses and seminars |
³ 9 cu |
|
Master’s thesis |
16 cu |
|
³ 80 cu |
|
Teacher in Computer Science |
|
|
Cum Laude Approbatur |
³ 55 cu |
|
Optional courses |
³ 8 cu |
|
Seminars |
³ 2 cu |
|
Master’s thesis |
10 cu |
|
³ 75 cu |
|
|
2. Minor subjects
|
|
|
General Computer Science, Software and Information Systems |
|
|
Mathematics: |
|
|
Approbatur, or |
15 cu |
|
Differential and Integral Calculus I, 11 cu |
|
|
Discrete Mathematics, or |
5 cu |
|
Algebra I, 5 cu |
|
|
Probability Calculus |
5 cu |
|
Logic I |
5 cu |
|
Optional courses |
³ 0 cu |
|
³ 26 cu |
|
|
Other minor subjects: |
|
|
Optional minor subject |
³ 15 cu |
|
³ 45 cu |
|
|
Applied Computer Science |
|
|
At least two minor subjects agreed upon by the student and the department |
³ 60 cu |
|
³ 60 cu |
|
|
Teacher in Computer Science |
|
|
Cum Laude Approbatur in another subject |
35 cu |
|
Pedagogical studies |
35 cu |
|
³ 70 cu |
|
|
3. Other studies |
|
|
Compulsory studies |
|
|
Orientation studies |
1 cu |
|
Second domestic language |
2 cu |
|
Foreign language |
1-2 cu |
|
Tutoring |
1 cu |
|
Courses free of choice |
³ 0 cu |
|
³ 5 cu |
Course descriptions of courses given in 1998-99
Approbatur
Computer Systems Organisation (3 cu)
Introduction. Data presentation, error detection and correction. Computer organisation. Conventional machine level. Assembly language. Compilation, linking, loading. Input and Output. Secondary storage. Operating system. Data communication equipment and software.
Information Systems (4 cu)
Principles of relational databases, SQL, database programming, application development, databases and the WWW, user interfaces, information system development, object-oriented analysis, use case model, introduction to database design.
Introduction to Computing (2 cu)
Introduction to computers and data processing. Algorithms. Computer hardware. Operating systems. Applications software. Programming languages. Database systems. Communication networks. System analysis and design. (The course was given also in Swedish and in English.)
Introduction to Programming (4 cu)
Basic principles of programming: algorithms, programming techniques, and object-orientation. The programming language Java.
Programming in C (2 cu)
Language definition. Programming tools. General programming principles.
Programming Project (2 cu)
The student designs, documents and programs a complete, realistic program. In the course of the development she/he also gives short lectures and demonstrations on the project.
Unix Principles (1 cu)
Principles of the UNIX environment for end users, including principles of file system, shell, wildcards, protection, I/O, text editing, regular expressions, sorting and searching, awk, program development, project maintenance, and networking commands.
Cum Laude Approbatur
Artificial Intelligence (3 cu)
General overview of the potential of AI in various kinds of problem solving is given. Main results in AI research and applications are presented. Also basic readiness to construct AI based software is provided. The course consists of overview, search and game playing, knowledge representation and reasoning, planning, probabilistic reasoning, rational decisions. Prerequisites: Basic ability to program in LISP.
Computer Graphics (4 cu)
Overview of graphics systems. Output primitives and their attributes. Two-dimensional transformations. Windowing and clipping. Segments. Interactive input methods. Three-dimensional concepts, representations, transformations, viewing. Hidden-surface and hidden-line removal. Shading and colour models. Modelling methods. Design of the user interface. Individual practical work.
Computer Uses in Education (4 cu)
Fundamentals of computer applications in education. The computer as a tutor, tool, and tutee. Computer assisted instruction (CAI) systems. Courseware design, development, and evaluation. Authoring systems and languages. Multimedia CAI. Intelligent CAI. Applications and research. Practical courseware designing in small groups. Compulsory for students in the Teacher subprogramme.
Concurrent Systems (4 cu)
Structure and implementation of concurrent and distributed systems. The main emphasis is on solving problems in operating systems.
CORBA architecture (3 cu)
CORBA architecture from the viewpoint of distributed systems. The IDL language. CORBA applications with Java and C++. CORBA services.
Data Communications (4 cu)
The electrical interface. Data transmission. Data link control protocols. Local area networks. High-speed and bridged local area networks. Wide area networks. Internetworking. Transport protocols.
Data Structures (4 cu)
Basic data structures. Applications to algorithms. Analysis of algorithms. Implementations of data structures and algorithms. Memory management.
Data Structures Project (2 cu)
A simulator or some other fairly large program is designed, programmed, tested and documented.
Database Systems I (4 cu)
Databases and database management systems. Relational databases, relational algebra and calculus. File and index structures. Query processing. Transaction processing. Relational database design, functional dependencies and normalisation. Object-oriented databases.
Digital Signal Processing (3 cu)
Basics of digital signal processing. Applications, especially in the area of natural sciences.
Information Systems Project (2 cu)
A small ADP-system is designed and programmed.
Management of Research Data (3 cu)
Metadata. Data presentation and storage: files, trees, databases. Statistical packages. Explorative data analysis. Sampling. Bootstrapping and randomisation. Data visualisation.
Programming Techniques (C++, 3 cu)
Abstract data types, class libraries, generic programming, object-oriented programming.
Scientific Writing (4 cu)
Sources of scientific information. Use of libraries and scientific databases. The structure and details of a scientific publication. Examples of scientific Finnish, Swedish or English. Three individual survey writing exercises.
Semantics of Program (3 cu)
Axiomatic semantics of programs. Weakest precondition calculus for the guarded command language of Dijkstra. Development of small programs based on the programming logic.
Software Engineering (4 cu)
Introduction to software engineering as a professional discipline. Models of software engineering. Team work. Project planning and organisation. Requirements analysis and engineering. Software design. Implementation techniques. Testing. Debugging and maintenance. Software configuration management. Software quality assurance.
Software Engineering Laboratory (6 cu)
Each student takes part in a project where a group of students analyses the requirements of a software product, designs, implements, and tests the product, using systematic software engineering methods and tools. The group assignment may also be focused on some sub-phase of the software life cycle, such as evolution or maintenance of an existing software system.
Theory of Computing (4 cu)
Finite automata and regular languages. Context-free grammars and languages. Rudiments of parsing theory and attribute grammars. Context-sensitive and type-0 grammars. Turing machines. Recursive and recursively enumerable sets. Computability and computational complexity. Compulsory for Laudatur students.
Unix Platform (3 cu)
The programming interface to the UNIX system: system calls and library functions for process control, memory management, file systems and peripherals, tools for interprocess communication.
Laudatur
Advanced Computer Graphics (2 cu)
A selection of advanced topics such as tray tracing, radiosity, solid modelling, illumination and colour, scientific visualisation, etc. are chosen as a course theme. Individual and group work, report writing and oral presentations by the participants.
Advanced Topics in Telecommunications Systems (3 cu)
Modern telecommunications systems: SS-7 protocol stack, Intelligent network – capability set 1, TINA architecture. Internet protocols: IPv6, protocols supporting mobility, quality of service in IP networks, real-time communication.
Compilers (5 cu)
Lexical analysis, syntax analysis, semantic analysis, and code generation, use of metatools, laboratory assignments.
Computational Biology (3 cu)
Molecular biology. Sequence comparison and database search. Fragment assembly of DNA. Physical mapping of DNA. Phylogenetic trees. Genome rearrangements. Molecular structure prediction.
Computer Architectures (4 cu)
Structure of computer architectures, from instruction sets to I/O systems. The main emphasis is on uniprocessor systems.
Data Security (3 cu)
Cryptography, public key cryptography and applications, data security protocols. Data security in TCP/IP networks.
Database Systems II (5 cu)
Physical data organisation in databases. Index structures for files. B-trees. Dynamic hashing. Query processing and optimisation for relational database systems. Join algorithms. Query optimisation for distributed databases. Crash recovery. Concurrency control. Transaction management in client-server architectures. Distributed transactions.
Design and Analysis of Algorithms (5 cu)
Analysis techniques. Design techniques. Models of computation and lower bounds. Algorithms on sets. Graph algorithms. Approximation algorithms for NP-complete problems. Probabilistic algorithms. Parallel algorithms.
Distributed Operating Systems (4 cu)
Kernel functionality. File service. Name service. Time and co-ordination. Replication. Distributed transactions. Recovery and fault tolerance.
Information Retrieval Methods (3 cu)
Traditional and new information retrieval methods, including networked retrieval and information exploration. Information filtering. Digital libraries.
Knowledge Discovery in Databases (3 cu)
Data mining. Finding frequent patterns in sequences. Integrity constraints in databases. Advanced techniques.
The LOTOS Specification Language (3 cu)
Lotos and its extensions. Specification and analysis of distributed systems. Lotos programming environments.
Machine Learning (4 cu)
History. Inductive learning: Learning in the blocks world, identification in the limit, version spaces. Learning classifiers: Finite automata, case-based learning, machine learning rules, decision trees, neural networks, genetic algorithms. PAC-learning: basics, Occam's razor, Vapnik-Chervonenkis dimension, learning by queries, PAC and noise, relation of different models. PAC and classifier learning. Inductive logic programming. Real-world applications.
Performance Evaluation (2 cu)
General performance modelling concepts. Queuing network models and their solutions. Workload modelling. Emphasis on applications.
Processing of Structured Documents (3 cu)
Structured documents (SGML/XML), models and languages for searching in, and formatting and transforming structured documents.
Robotics (4 cu)
Types and applications of robots. Components of a robot. Architectures. Autonomous mobile robots: Navigation and motion planning. Robot learning: Reinforcement learning, Q learning.
Simulation Methods (2 cu)
Simulation in modelling of computer systems. Simulation models and implementation. Generation of random numbers. Estimation and computing of parameters in measure data. Basics in result analysis.
Spatial Information Systems (3 cu)
Spatial data and geographic database systems. Topology of planar graphs. Spatial data types based on finite-resolution geometry. Spatial index structures. Spatial joins. Space-filling curves and the Peano model. Topological relationships. Constraint databases and the polynomial model. Object-relational spatial databases.
String Processing Algorithms (4 cu)
Exact string matching. Approximate string matching. Pattern matching in static strings. Text databases and hypertext. Algorithm implementation and a comparison project.
Three Concepts: Information (4 cu)
Information theory. Shannon’s source coding theorem and noisy channel coding. Data compression. Bayesian inference.
Three Concepts: Probability (3 cu)
Bayesian probability. Degree-of-belief interpretation of probability. Example tasks of probabilistic modelling. Graphical models.
Transaction Processing (4 cu)
Serialisability theory. Locking and non-locking schedulers. Multiversion concurrency control. Centralised and distributed recovery. Management of replicated data. Multidatabase transaction management. Co-operative transaction management. Prototype systems.
User Interfaces (4 cu)
Concrete user interface solutions and their foundations. Aspects of user interface design: cognitive psychology, graphical user interfaces, user interface management systems, usability and testing. Current fields of research, e.g., WWW, multimedia, computer-supported co-operative work, virtual reality.
Seminars
(each 2 cu)Adaptive Information Systems
Computer Graphics
Computer Uses in Education
Object Architectures
Research in User Interfaces
Research in Object-Oriented Languages
Research Seminar on Agent Technology
Research Seminar on Bayesian Networks
Research Seminar on Computational Biology
Research Seminar on Nomadic Computing
Semi-Structured Data
Telecommunications
Telecommunications Technology
Other studies
Tutoring (1 cu)
In tutoring the second year students are divided into groups of ca. 15 students. A teacher or researcher (tutor) leads each group and the group meets monthly during two academic years. During the meetings students introduce matters related to their studies for discussion. In addition each student meets regularly with her/his tutor for private discussions to solve problems in her/his studies. The objective of tutoring is to reduce the number of dropouts, uncover bottlenecks in the studies, and improve the relationships between students and teachers.
Appendix A.2: Research and development projects since 1.1.1998
The research at the department has evolved over the years in step with the international research trends in computer science. Early work in numerical analysis in the 1960's made room for work in programming languages and compilers in the 1970's. Since then the research has diversified and its volume has increased.
The main sources of research funding are the Academy of Finland, the National Technology Agency (TEKES), the Ministry of Education and the European Union (EU) research programmes. All projects funded by TEKES also have partial funding by industrial partners.
The Department participates in two graduate schools that fund the research of some PhD students: The Helsinki Graduate School in Computer Science and Engineering (HeCSe), a joint school with the Helsinki University of Technology); and the Graduate School in Computational Biology, Bioinformatics and Biometry (ComBi) a joint school with the University of Turku and the Center for Scientific Computing of Finland. ComBi is co-ordinated by the Department and directed by Prof. Esko Ukkonen.
The department has three subprogrammes and five lines of specialisation that are used in the planning of the curricula and in administration. The division is not strict, and several research projects span two sections. The sections cover roughly the following subject areas:
Computer Science:
- Algorithms (Prof. Esko Ukkonen, Prof. Matti Mäkelä): algorithms and data structures, computational complexity, computational geometry, machine learning, computer graphics, numerical and symbolic computation, computational biology, geoinformatics, computationally intensive tasks.
- Intelligent Systems (Prof. Henry Tirri): Bayesian networks, intelligent and adaptive systems, artificial intelligence, computational intelligence, artificial life.
- Software Engineering (Prof. Jukka Paakki, Prof. A. Inkeri Verkamo): programming languages, compilers, software engineering, performance evaluation.
- Distributed Systems and Data Communication (Prof. Kimmo Raatikainen, Prof. Timo Alanko, Prof. emer. Martti Tienari): formal specification and verification, distributed systems, computer networks, operating systems.
- Information Systems (Prof. Hannu Erkiö, Prof. Pekka Kilpeläinen, Prof. Seppo Sippu): databases, human-computer interfaces, computer supported co-operative work, information system design methodology, design of databases, text databases, object-oriented databases, logic databases, database structures and algorithms, document management, data mining and knowledge discovery, management of spatial data (GIS).
- Applied Computer Science (Prof. Esko Ukkonen): computational biology, geoinformatics, computationally intensive tasks.
- Teacher in Computer Science (Computer-supported education, Prof. Pekka Kilpeläinen): computer-aided instruction, computers in education
Applied Computer Science:
Teacher in Computer Science:
In the following, the research activities of each section of the department are reviewed.
Algorithms
The main research areas are algorithms and data structures, machine learning, probabilistic reasoning, computations by complex dynamic systems (cellular automata and genetic algorithms) and computational biology. Algorithms, Data Structures and Complexity (Academy of Finland, 1983-, Ukkonen) is the area with the longest tradition. The work on string matching algorithms (Ukkonen, Tarhio, Kärkkäinen) has been particularly successful. Theoretical work has often been conducted within the framework of systems research providing practical motivation for the problems studied. Currently, special emphasis is given to the research on algorithmic problems in computational biology and bioinformatics. A project on Algorithmic Methods of Biocomputing and Data Analysis (Academy of Finland, 1999-, Ukkonen) has just started.
The Machine Learning Group (Academy of Finland, 1994-, Mannila, Ukkonen, Elomaa, Kivinen) has studied different machine learning models and the complexity of learning tasks within these models as well as their applications, e.g., in biological sequence analysis and process industry. The aim of Neural and Computational Learning (NeuroCOLT Working Group/EU, 1994-2000, 10 sites, Ukkonen) is to develop a fundamental understanding of learning and of when and how it can be implemented algorithmically. Machine Learning Methods in Hydrological Modelling and Optimisation (Academy of Finland, 1994-99, Ukkonen) applies machine learning methods in hydrological modelling (a joint project with the Finnish Environment Institute).
Intelligent Systems
The Complex Systems Computation Group (CoSCo, Tirri, Myllymäki) studies computational issues related to complex systems focusing on prediction and model selection issues. Current work of the CoSCo group is concentrated on theory and applications of Bayesian (belief) networks, and related probabilistic model families, such as finite mixture models. The Computationally Intelligent Hybrid-Paradigm Environments project (HYPE/TEKES, 1995-98) studied hybrid systems integrating different modules such as neural networks, probabilistic models and genetic algorithms all aiming at solving a single problem. The general objective of the Computational Intelligence Techniques for Non-linear Modelling in Social Sciences (NONE/Academy of Finland, 1998-99) project is to develop theoretically sound computational intelligence techniques for non-linear modelling of data, and methodologies for applying them in the domain of educational data. The main objective of the PROMISE project (TEKES, 1998-99) is to study methods for applying probabilistic modelling techniques (Bayesian networks, finite mixture models) and stochastic optimisation methods (simulated annealing, genetic algorithms) in constructing adaptive and intelligent systems.
Software Engineering
The research in software engineering, carried out by the Research group on Object-Oriented Software Architectures (ROOSA: Paakki, Verkamo, Tuovinen, A. Viljamaa), concentrates on software architectures from different perspectives. The group runs currently three externally funded research projects: The Framework Editor project (FRED, TEKES, 1997-1999) develops techniques and tools for designing object-oriented application frameworks based on design patterns. The Software Architecture Analysis, Recovery and Assessment project (SAARA, Academy of Finland, 1999-2001) studies methods for automatically recovering architectural knowledge from source code. The Metrics for Analysis and Improvement of Software Architectures project (MAISA, TEKES, 1999-2001) develops methods and tools for the measurement of software quality at design level. The group and its research projects have close contacts to Nokia Research Center where Prof. Paakki is a manager in the large European EUREKA/ITEA project ESAPS on software architectures and system families.
The group has also been running a number of projects that no longer get external funding but that still partly exist in the form of graduate studies. The Channel into Object-Oriented Protocol Design project (Kannel, TEKES / Academy of Finland, 1993-1996) developed an integrated language for the design and implementation of communication protocols. The Computer-Aided Software Maintenance project (HyperSoft, TEKES, 1994-1996) developed a hypertextual tool supporting typical software maintenance and program comprehension activities.
Distributed Systems and Data Communication
Mobile Computing (MOWGLI/TEKES, 1993-99, Tienari, Raatikainen, Alanko, Kojo) studies, designs and tests new data communication architectures for GSM-based mobile data services. The Service Machine Development for an Open Long-term Mobile and Fixed Network Environment project (DOLMEN/EU/ACTS, 1995-98, 12 partners, Raatikainen) developed a solution to enhance CORBA for wireless access and terminal mobility based on the concept of interoperability bridges described in the CORBA 2.0 architecture. The Adaption Agents for Nomadic Users project (MONADS/TEKES, 1998-, Raatikainen) examines adaptive agents for nomadic users. Mobile Intelligent Agents in Accounting, Charging and Personal Mobility Support (MONTAGE/EU, 1998-, 5 partners, Raatikainen) aims to research, evaluate and assess the impact of agent technology to the telecommunications world. A new project, Promoting Interoperability for Multimedia services in Europe (Prime/EU, 1998-2000, 8 partners, Raatikainen) has just started.
The Modelling of Concurrency (MOCO/Academy of Finland, 1990-, Tienari, Kaivola) studies formal specification and verification of distributed systems, developing and using theories and software tools based on process algebras and temporal logic. The Open Distributed Computing Environments (ODCE, 1992-, Tienari, Raatikainen, Kutvonen) group concentrates on open architecture models and platforms. First, the DRYAD project (TEKES, 1992-1996, Tienari) studied middleware support for federation of sovereign systems. Conceptual results were contributed to the Open Distributed Processing reference model standardised by ISO/ITU; experimental results included a prototype trader. A newer ODCE project, the CORBA-Based Framework for Telecommunications project (CORBA-FORTE/TEKES, 1998-1999, Tienari, Raatikainen) focuses on the performance and usability of the CORBA architecture in telecommunications systems.
The research project Database Architecture for Intelligent Networks (Darfin/TEKES, 1993-95, Raatikainen) examined database architectures that can fulfil the requirements of Intelligent Networks (IN) and Telecommunication Management Networks (TMN). The research project Real-Time Object-Based Database Architecture for Intelligent Networks (RODAIN/TEKES, 1996-, Raatikainen) continues the work done in the Darfin project. In the project the research group has designed and specified a real-time object-oriented database architecture for Intelligent Networks and implemented a simple prototype.
The worldwide development of the LINUX operating system was initiated and co-ordinated at our department by Linus Torvalds 1991-97. The work with Linux still continues here. The objective of the department in the High Performance Gigabit I2O Networking Software project (HPGIN/EU, 1998-2000, 3 partners, Raatikainen, Tienari) is to implement I2O extensions to the Linux standard network operating system and to add support for I2O compliant gigabit networking adapters.
Information Systems
In information systems the largest research project has concentrated on data mining (Mannila, Toivonen, Verkamo, Klemettinen), also known as knowledge discovery in databases. The research is done with the machine learning group, with statisticians, and with the appliers. The research started in the late 1980's in the context of developing tools for inferring integrity constraints from databases. Recent research results include efficient data mining methods for database re-engineering, methods for finding recurrent episodes within event sequences and development of automatic tools for the simulation of complex statistical models. The Data mining in telecommunications project (TASA/TEKES, 1994-97, Mannila, Klemettinen) has developed several new methods for extracting interesting information from large data sets. The From Data to Knowledge project (FDK/Academy of Finland, 1996-99, Mannila, Toivonen, Ukkonen, Verkamo,) is a large umbrella project developing methods for knowledge discovery from large masses of data. The project combines and develops methods in computer science and statistics, and the methods are applied to epidemiology, biotechnology, environmental research and archaeology. Knowledge Extraction for Statistical Offices (KESO/EU, 1995-98, 8 partners, Mannila, Verkamo) developed tools for knowledge discovery from large statistical data sets.
The Document Management (DocMan, Mannila, Kilpeläinen, Ahonen, Lindén) research group studies the theory and application of structured documents. Former research projects include the sgrep project (1995) which designed and implemented a search tool for structured documents. Structured and Intelligent Documents (SID/TEKES 1995-98, Kilpeläinen) was a project within the DocMan group that studied and developed methods and tools for the realisation of ''intelligent documents'' which would easily adapt to the needs of different users. A central goal application was document assembly, by which we mean computer-supported compilation of new documents from existing text sources. The Intelligent Management Information Systems (ÄLYJO/TEKES 1997-99, Mannila) project studies information retrieval, computer-supported co-operative work and interactive communication in management information systems.
The Transaction Management Support for Co-operative Applications (TRANSCOOP/EU, 1994-96, 3 partners, Tirri) project studied design of co-operative systems including the description and formal specification of co-operative activities.
Applied Computer Science
Applied Computer Science is pursued in several of the other research divisions, e.g., within the algorithmics, machine learning, biocomputing, and data mining groups.
Teacher in Computer Science
The Animation Aided Problem Solving (AAPS/Ministry of Education 1996-98, Tarhio, Sutinen) has studied program visualisation, teaching algorithms by means of animation, and computer-supported concept mapping. The group has developed a Web-based system for fast generation of algorithm animations. The Survey of Information Technology in Human Services in Finland (SosKart/STAKES, 1998-99, Mäkelä) analyses and evaluates the state of the art and the prospects of the information technology applications currently used in human services in Finland.
B. SELF-ASSESSMENT: THE EVALUATION OF THE QUALITY OF THE PROGRAMME (FACULTY)
- THE FRAMEWORK
- PROGRAMME
- PROGRAMME/DEPARTMENT STAFF
- PROGRAMME STUDENTS
- TEACHING AND LEARNING
- ASSESSMENT OF STUDENTS
- STUDENT SUPPORT AND GUIDANCE
- LEARNING RESOURCES
- CO-OPERATION AND NETWORKING
- QUALITY MANAGEMENT AND ENHANCEMENT
- PRACTICAL ARRANGEMENTS
Strengths. The department is the largest and one of the oldest computer science departments in Finland, and it has a long tradition in both teaching and research. The range of courses in different specialisation areas is large. Several research groups rank very high internationally. Facilities are good (if not excellent) as has been outside funding during recent years. The staff is young and co-operation with industries and other universities extensive.
Weaknesses. The department is geographically rather isolated from other departments of the university as well as industries. It has insufficient visibility among high school students who tend to choose a technical university instead. The university has decreased the basic funding during recent years (due to national economical regression) and the basic funding does not cover all of the full-time teacher positions any longer.
Opportunities. The department has been very dynamic during the last two years. Staff groups have been discussing and planning the research and teaching as well as the image of the department. Many new ideas have been presented, out of which the department has started implementing a few. The IT field seems to continue growing in Finland, which also makes the programme more attractive. For the department, increasing visibility means improving possibilities for outside funding. This is already true for the research: the number of research projects is steadily growing
Threats. There is a risk that the basic funding decreases even more as it tends to be based on the number of graduates. However, as long as the IT field employs students at the current rate, the graduating part of the students will stay fairly small. Industries also employ many of the teachers.
Strengths. The programme is very extensive providing a broad level of basic education and many specialisation areas in computer science. The programme gives a strong background for researchers, but students also compete for positions in the industries on the same line as students from other universities and technical universities. The programme is both theoretical and practical.
Weaknesses. Few students graduate even if the intake is large. Some enterprises (mainly small ones) also consider the programme too theoretical.
Opportunities. A new curriculum has been introduced in 1999. The department hopes that it will remove some of the bottlenecks that keep students from graduating. The department has also been reorganised into three subprogrammes of which Computer Science is divided into five specialisation areas. All subprogrammes (specialisation areas) have their own person in charge. This is expected to have a positive effect on the programme as a whole by giving the research groups more self-awareness and by better defining the synergy between different specialisation areas.
Threats. The new curriculum is only now being tested and there is no evidence yet whether it will fall out well. It might turn out to be too extensive if the number of staff decreases.
Strengths. The department employs an overall staff of about 110 teachers, researchers and technical personnel. Some top researchers of international level have emerged at the department and a few teachers have been awarded prizes for their pedagogical skills or their teaching material.
Weaknesses. Employment in the IT field has been very good during the last five years. Industries have employed many of the teachers and researchers of the department. The income level in industries is substantially higher, and even other universities (especially the Helsinki University of Technology) tend to provide better working conditions to our teachers (less teaching, more research, higher income, more independence). The department has difficulties in finding qualified staff, and the teachers are burdened with too much teaching. The department would also need more senior researchers to supervise the increasing number of graduate and postgraduate students. Even if the basic funding has decreased, during recent years there has been an increase in outside funding; however, because of the shortage of qualified teachers and researchers, the department has not been able to take full advantage of this.
New teachers are usually employed for one term at a time. This has led to some insecurity among the teachers and it has also been easier to leave the department for a "steady" job. Most teachers are employed while they are still students at the department, and many of the teachers have not worked outside the department. Many student teachers also make slower progress in their studies due to their teaching burden.
Opportunities. The university has introduced a new system of a working year of 1,600 hours. Instead of fulfilling a certain teaching quota (e.g. 20 hours/week), a teacher can perform other tasks as well (such as research, administration, etc.) within the 1,600 hours. The new system does not decrease the teaching requirements at the department, but it might help to redistribute teaching loads between teachers. Research groups now also encourage their members to take part in the teaching to decrease the teaching load of the full-time teachers.
The department is at the moment discussing a focusing of its specialisation areas. Each specialisation area has a professor in charge and every employee will be assigned to one (or more) areas. The members of a specialisation area are responsible of the teaching in that area. The professor in charge will also work as a direct superior to the employees in the area. S/he will, for example, be in charge of the career development of the staff.
The university will introduce a new equalised position hierarchy among the teaching staff. In the future there will be teachers/researchers at four levels: professors, university lecturers, research assistants (post docs) and assistants (graduate positions). It is still unclear how this change will affect the department.
The department has taken a stand this autumn to encourage teachers to participate in the personnel education available at the university (e.g. pedagogics). The teachers are also encouraged to take part in conferences.
Threats. Between the universities the competition to employ the best teachers has become ever more noticeable. In the short run, the department may lose still more teachers to other universities (and industries). The increasing outside funding leads to more research positions, and teachers choose research instead of teaching. Student teachers are given too heavy workloads and never graduate, which decreases the number of degrees per year.
Strengths. Many of the department’s students belong to the top range of students in Finland. They usually have a good background in mathematics and natural sciences from high school.
Weaknesses. Again, due to the very good employment in the IT field, many students leave for positions in the industries before they graduate. Even students who are only in their second year may hold full-time positions outside the department. Often they make slow progress in their studies, and in many cases they never graduate. The department has tried to satisfy the need of IT employees by increasing the intake of students yearly, but only about 30% of the students ever graduate, and those who do, take an average of 7.3 years to complete their master’s degree. Also too few postgraduate students complete their doctoral studies.
Opportunities. The department is trying to focus both on undergraduate students and on students in high schools to improve its weak visibility. The department will participate in peer tutoring to increase the awareness of the department among its own students. The department will also support student groups who visit high schools in Finland informing about the Computer Science Programme. The (rather new) graduate school system will help postgraduate students to complete their licentiate and doctoral degrees in shorter time.
Threats. The employment in the IT field seems to continue to be very good. There is a risk that the situation will stay the same for a long time; students continue to put work before their studies. Fewer students graduate and fewer stay on to become researchers. There is also competition between the universities: which university can entice the best students. In the short run, again the department might lose the best students to the technical universities.
Strengths. The range of courses is very large. The students can choose between many specialisation areas in their graduate studies. One or more research groups are in charge of each specialisation area. The curriculum has recently been changed to better correspond to the research areas of the department and to the demand of the students. Many courses have been split into two consecutive courses. This arrangement has increased the flexibility in combining the needs of basic and specialised education. The supervising of project work has been improved to support students better.
Weaknesses. Due to the large intake of students, basic courses are very large. These courses take resources from other teaching and research. To name an example, the department cannot afford too many optional courses. On the other hand, teaching larger groups is more difficult and there are many dropouts. Courses mainly consist of lectures and exercises, where lectures only require passive attendance, and it is questionable how much the students assimilate of what is taught.
Opportunities. Small changes in the teaching have already been made, but still more practical projects would give a better understanding of topics. The new curriculum also tries to remove redundancies in the courses. There is also hope that course material would stay the same for at least two consecutive years and that students could be informed about the material well beforehand. The department could also give courses in social and legal aspects of computer science, perhaps in co-operation with other departments. With the new curriculum, the department has taken a step towards periodic teaching. The next step could lead to problem-oriented teaching.
Threats. There is no experience from the new curriculum and there is a risk that it leads to more administration work for the already overloaded teachers and to a lack of conformity in the courses.
Strengths. The assessment methods have been fairly homogeneous and usually easy to understand.
Weaknesses. Most courses have been assessed on written exams and on the number of solved exercises. In some cases, however, exams and exercises are not the best methods for completing a course. There have also been discrepancies in completing courses. Students who complete a course by mid-term exams must take exercise sessions, while students who only take an end-term exam are not required to do any exercises.
Opportunities. Some new assessment methods have already been introduced, such as small project works and writing learning diaries. The department is now investigating web-oriented teaching on a larger scale.
Threats. New methods require new knowledge. The new assessment methods must not trivialise the assessment and make it too easy for the students to complete the courses
Strengths. Tutoring by teachers was recently introduced. The tutoring is compulsory for students majoring in computer science. There are also five student counsellors at the department, and all teachers have regular office hours for students.
Weaknesses. Finnish students seem to be rather independent, learning from their own mistakes rather than seeking advice from the student counsellors. Curriculum changes as well as changes in the application routines, etc. make it difficult for the counsellors to maintain their knowledge of student affairs up-to-date. There have been rather few (and not very well attended) informal seminars introducing the department and its research to the undergraduate students.
Opportunities. There is hope that tutoring will provide the students with information about the department and its research in an early stage before the students leave for positions in the industries. By participating more in peer tutoring, the department hopes to influence its own students as well as prospective students still attending high school. The department could try to follow the progress of the students more closely, e.g. by requiring every student to set up a study plan yearly.
Threats. The large intake of students puts pressure on the counsellors and tutors and there is less time for each student.
Strengths. The department has fairly good facilities. Its library has long been the largest computer science library in Finland. The computing facilities of the department have been professionally maintained and working well, better than at other departments of the university.
Weaknesses. The library funding has decreased during the last years and the collections are slowly going out-of-date. There are too few computers for the students and it is also difficult to find qualified computer personnel for maintaining the computers that are available. The computers become obsolete rather quickly and must be renewed in three years. The premises are also becoming too small.
Opportunities. New larger facilities will be built in the Kumpula campus area (close to the Departments of Mathematics, Physics, and Chemistry), but it is still unclear when this will happen. Some new facilities have been made available in the building where the department is currently located, and there are plans for additional computer classrooms, staff rooms and more library space.
Threats. The department may outgrow its current premises as well as the future Kumpula buildings (such as planned) if it continues growing at the current rate.
Strengths. Co-operation has increased during recent years on all levels. The department now co-operates with other Finnish universities within the graduate school system and the system of flexible studies. The department also participates in the major international student exchange programmes. Co-operation with industries is extensive, as is research co-operation with other Finnish and foreign universities. Within the EU research frameworks, the department also has many foreign industrial partners.
Most research groups are large enough to reach international results but yet maintaining their manageability.
Weaknesses. The department is located rather far from the other departments and faculties of the university. This makes it difficult for students doing cross-scientific studies. Important industrial partners are also far away (with a few noticeable exceptions).
The department has a long tradition of being self-sufficient. The academic tradition is slowly changing in favour of increasing co-operation with the industries.
Opportunities. Co-operation with other departments has in the last two years increased. It could still be increased both with industries and other universities. The department is closely located to the Finnish Telecom Company Sonera with which the department already co-operates. Further co-operation could be considered. When the department moves to the Kumpula campus area it will be closely located to several other departments of the Faculty of Science.
Threats. Outside funding and close co-operation with industrial partners as well as university institutions both redirect the research of the department and make the universities and technical universities fairly similar in both education and research. By moving to Kumpula, the department will again be far away from most industrial partners.
Strengths. The department maintains an automatic feedback system for the students, with which they can anonymously praise or criticise the teaching of the department. Both the teachers and the steering committee of the department process the feedback to improve the teaching.
Weaknesses. The feedback system has not been too popular among students, who tend to forget or do not bother to use it. In some cases, the standardised system does not fit a certain course, and feedback that is given after the course has finished does not help students who already took the course.
Opportunities. The feedback system will be changed to accept feedback twice a term. This will give the teacher a chance to change the course while giving it.
Threats. Many courses now only last half a term and feedback given twice during a term will still not help students taking a certain course.
Strengths. During one year (1998-99) there have been several evaluations of the department (internal evaluations of the teaching and of the research, evaluation for centre-of-excellence status by the Academy of Finland). The department has already had to answer some of the questions raised in this evaluation. Some of the answers have been reused (slightly modified) for this evaluation. The department has also held several planning meetings among the staff for rethinking strategies for teaching, research and overall image.
As a very large department, it has had the resources to employ one administrative person for managing the evaluation answers and the contacts to the evaluators or evaluating boards.
Weaknesses. Rather few persons have been involved in writing the evaluations. This might distort the contents of the evaluation answers.
Opportunities. Four evaluations during one year have pinpointed some of the strengths and the weaknesses of the department. With the evaluations as a base it should be easier to improve the activities of the department.
Threats. The evaluations of the department have been extensive. The department must be able to use them in the right way. Too many evaluations during one year might result in a negative reaction from the staff (and the students).
C. SELF-ASSESSMENT: THE EVALUATION OF THE QUALITY OF THE PROGRAMME (STUDENTS)
1. THE FRAMEWORK
Strengths. The amount of basic funding collected from the private sector is increasing. The positive aspect of this development is that courses are more actively planned to face the realities of the market world. A student may have a broader variety of options to choose from and is in a position to compete on equal terms on the job market after graduation.
Weaknesses. Platform independency provides a broader base of knowledge but causes difficulties in adjusting to working life.
Opportunities. Enhancing the interaction between the industry sector and the field of practical computer science could be a way to motivate studying: having a realistic idea of what is to come and what kind of skills are needed in working life give a meaning to the studies.
Threats. The faculty will have to deal carefully with non-governmental funding. A university, the funding of which is largely based on money from the private sector, may lose its independent nature as provider of education.
2. PROGRAMME
Strengths. The programme supports students by giving them wide theoretical knowledge without dependency on any specific developing-tools on the market.
Lately the possibility of dividing courses into smaller parts is an improvement. Courses are easier to adapt to meet the challenges of a changing world, and a limited material is easier to learn. Choosing the order in which courses are taken also becomes easier.
Weaknesses. The independency of specific tools may turn out to be a disadvantage when applying for a certain kind of job. The department might consider the possibilities of letting senior students use available tools when well argued for.
Opportunities. Students have the opportunity to specialize in research which surely is an additional incentive for those with the ambition and skills. Participating in research groups on a relatively early stage may well further one's studies at least in areas connected to the research topic. The writers of this report are unaware of the possibilities for a student who has not applied for the prospective researcher programme to participate in research at later stages of her/his studies.
Threats. Although research may appeal to many, the great difference in income levels is putting people's ideologies to the test. A safer career in the business world does indeed make people turn away from the opportunity to work as a researcher at a university.
About the change in the first programming language to be taught: It is good to keep up with progress, but students with a different language background may have difficulties in adjusting to the courses which require the new language.
3. PROGRAMME/DEPARTMENT STAFF
Some of the teachers are well motivated and tend to inspire the students as well. On the other hand, many seem to lack even the basic pedagogic teaching skills, resulting in obscure courses that are hard to follow. In these cases, even the most interesting subject may become quite objectionable.
Some students are also part of the department staff, mainly as part-time teachers. While giving guided exercises they gather valuable teaching experience. They also have the advantage of having their own studies in fresh memory and have good knowledge of possible problems the average student may be facing, thus being able to adapt their guidance to the students’ needs.
As a conclusion, it should be stated that because very few have been born with the gift of teaching, all personnel should be given the proper education on this subject.
4. STUDENTS
Strengths. The marketing and communication of the department has improved recently and the overall impression is quite positive.
The employment rate in the field is quite good.
Students who have been accepted from the Open University of Helsinki are quite motivated to graduate.
Weaknesses. The image of the department falls behind when compared for example with the Helsinki University of Technology.
Admittance to the department is so easy that the department has in some cases become just a place to spend a year while the student waits to be accepted at another educational programme site s/he is more interested in. Too many students quit before graduation.
Opportunities. The broad base that our department offers could also be seen as a strength if marketed the right way.
Threats. Graduates and even under graduates have good job opportunities. The image competition with the Helsinki University of Technology is a threat as well as a possibility.
5. TEACHING AND LEARNING
Strengths. The department does have a few very skillful teachers who are willing to share their knowledge and encourage students to think by themselves (Arto Wikla, Sari Laakso to mention a few). The material on courses is usually well compiled and the information needed can easily be absorbed.
Weaknesses. A course book is mandatory in nearly every course, even if self-made material could be put on the same level without greater cost. These additional expences can force students to work during their studies.
For some lecturers motivation is a problem, which can affect the quality of the course material and its processing as well. Some of these lecturers have the habit of just reading out loud the very same text that can be seen on the screen. This is usually quite frustrating and does not motivate people in their studies.
A course where the methods of learning are discussed is not provided. Adding such a course to the study program would be a clear improvement since many of the students seem to bring up this subject.
The use of computer resources as part of the learning process has not been standardized. More of the material that the department supplies should be in the World Wide Web for the students to look for.
Opportunities. The fact that each student has easy access to WWW is an advantage which should be utilized. Having course material available in the web would save time for many students and therefore is a short-term goal that the department should pursue more vigorously, although some teachers have already used this method in the past.
The fact that the lectures do not interest some people clearly indicates a pressing need to reform the teaching methods. If the material of a lecture can be easily assimilated by the students themselves why not devote parts of lectures to presenting the practical solutions of a certain issue.
More emphasis might also be put on the teacher providing questions and stimulating discussion and thus helping the students to focus on the relevant topics.
The library is an asset that could be better taken advantage of. The possibilities offered by the library unfortunately remain vague for many students. Offering up-to-date information in the areas relevant to their studies could be a way to awaken the interest of students.
Foreign languages (English) should be used more often when teaching the exercise groups. This has already been an option in most of the courses, but probably the lack of attendance is due to the nonexistent support and encouragement by the department. In the future, the interaction between people from different countries will increase and the ability to communicate verbally in foreign languages will be more important than today.
Threats. Difficulties in hiring new staff (especially teachers) may result in a lower level of education.
6. ASSESSMENT OF STUDENTS
Strengths. Assessment is usually based on the success of a particular student in one or more exams and her/his participation in exercises although the practice may vary in each particular course — in some courses there are several alternative assessment frames. The grounds for assessment are clearly presented to the students before the course, or at the first lecture at the latest, save some exceptions, thus enabling the students to better plan their time and other resources in advance.
Students are usually assessed fairly with no one being favoured. The evaluation team did not recall one instance where someone had complained of unfair grading compared to someone else attending.
Some courses practice very effective individual feedback to the students on their progress. As an example, on the User Interfaces course of spring 1999, students were given personal feedback on their performance in given exercises as well as detailed evaluation of their progress during a course related prototype construction.
Teacher tutoring is the main forum for evaluation feedback for students and the only visible monitoring system of studies. In both group and private meetings the desires, goals and performance of an individual student and all students together are discussed and reviewed. This often helps students to put their own progress and goals in perspective and on track.
The evaluators were unaware of the use of study diaries, which are used in some courses, as well as of grading.
Weaknesses. The assessment is usually limited to exams and exercises with very quantitative measurements. These measure the ability of the student to remember the theory, examples and details of what has been presented, more than the capability of the student to truly understand and creatively apply what s/he has learned.
The mandatory exercise attendance, enforced by many lecturers limits the freedom of students to practice the learning methods most suitable for them. Although everything may not be assessed by exams or learning diaries, the mandatory attendance is often more a custom than a necessity.
The feedback on student assessment in laboratory works and courses is most sparse. Usually a student is given her/his grade and the distribution of all grades at the most — occasionally, there is some feedback during laboratory exercises.
Opportunities. Students who attended the aforementioned User Interfaces course have said they were greatly motivated by the feedback and the apparent commitment of the course staff. Given adequate resources, this level of effort might enhance the learning overall.
The teacher tutoring is seen as a great promise — an opportunity to do much more. Currently the tutoring is quite lapse with few meetings over all too short a time period. It is believed that by long term monitoring and guidance the impact on the studies of students would be much greater. Also more in-depth discussions and analyses might make the tutoring more personal to the student, and thus more effective.
Some lecturers already make the effort and prepare the exams so that they measure the understanding and the ability of a student to apply the theory learned during the course, rather than just test what each one can remember. These kinds of exams should be encouraged to better assess the progress of students and various teaching methods. This principle could also encourage students, who take mainly final exams without participating in the course, to focus more on learning than on memorising.
Threats. The evaluation team found no conceivable threats.
7. STUDENT SUPPORT AND GUIDANCE
Strengths. Tutoring by teachers has started valuable conversations between the department and its students.
The basic routes to graduation are clearly and well understood by the students.
Weaknesses. More information should be available about the different routes and possibilities for graduation at the very beginning of studies. For example, what minor subjects are possible in which situations. Usually this seems to be quite obscure for students, so they will just choose the subjects that the department suggests.
The department should better inform students about interdisciplinary studies. These might give a lot more boost for the students who are not so fond of research and want to have a little broader aspect of life.
Neither skills to improve effectiveness of studying nor social skills, are currently teached at the department, nor directly suggested by tutors or the student guide.
Opportunities. A more individualistic view of different study possibilities might give the department the boost it needs to achieve new teachers and researchers as well as increase the amount of graduated students.
Threats. The large intake of new students creates a lot of pressure for teacher-tutors as well as does the changing of study requirements .
9. CO-OPERATION AND NETWORKING
Strengths. We are independent from the industries. Industrial enterprises also offers numerous possibilities for students to complete their studies with a master’s thesis.
Weaknesses. The department is physically located quite far from other departments and universities. The possibilities of JOO-studies are not understood well enough at the Department.
It seems that foreign exchange students are left to their own devices too much.
Interaction between the industries and an individual student is quite minimal. The department and its students are not as well known to the industries as students of the Helsinki University of Technology.
Exchange teachers do not seem to lecture enough. It would be valuable for the students to get different views on the matter studied.
Opportunities. Opportunities to study minor subjects from other fields of science could give a more individualistic view-point to the studies.
It is relatively easy for an exchange student to leave. Exchange students coming to the department could give valuable information on different cultures and models of behavior and thinking.
Better cooperation with the industries might give the department better financial resources.
Threats. Students have to take a lot of responsibility in the JOO-studies, because the department does not. The department cannot guarantee that the necessary courses to complete the minor studies are accepted by the JOO co-operation partner.
Too much co-operation with industrial enterprises might lead to similarity between different universities.
10. QUALITY MANAGEMENT AND ENHANCEMENT
Weaknesses. Students rarely get to know if their feedback has been noticed or ignored.
Opportunities. The department should supply a resource for anonymous feedback on any issue. It would be a channel for the students to give general feedback of issues concerning the department. Some people (possibly students) would sort out the more serious ones which could be handled as part of the board meetings.
Teacher tutoring has been noted as a natural place for the students to speak about their problems and concerns. Utilizing this feedback might give good results.
Threats. Teacher tutoring is the main forum for evaluation feedback for students and the only monitoring system of studies visible to them.
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In both group and private meetings the desires, goals and performance of an individual student and all students together are discussed and reviewed. This helps many to put their own progress and goals in perspective and on track.
The evaluators were unaware of the use of study diaries, which are used on some courses, besides of grading.
11. PRACTICAL ARRANGEMENTS
Strengths. In principle the idea of self-assessment was sound. Creating more discussion within the department is always beneficial.
Weaknesses. The self-assessment programme faced slight problems when it comes to the student participation. When asking people to do the job, it was said to be much simpler than it proved to be. This caused much haste in finishing the assignment properly.
Opportunities. Using hired people to organize the students' part could ensure a better result.
Threats. If the student groups assigned to the evaluation is to be as small and unorganised as now, the results of the assignment can be distorted and express only the personal opinions of a few people instead of the majority’s.
Names and positions of participating persons:
Students
Marko Saaresto, Joanna Mrozinski, Minna Majuri, Niko Lindqvist, Antti
Martikainen, Kirsti Maaniemi, Veli-Pekka Kestilä