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Learning ICT during an introductory programming course at Tumaini University, Tanzania

Learning ICT during an introductory programming course at Tumaini University, Tanzania. Mikko Vesisenaho Department of Computer Science, University of Joensuu, Finland . Background information about the country. 5.8 % secondary education, 1.1 % tertiary education (World Bank, 2001)

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Learning ICT during an introductory programming course at Tumaini University, Tanzania

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  1. Learning ICT during an introductory programming course at Tumaini University, Tanzania Mikko VesisenahoDepartment of Computer Science, University of Joensuu, Finland

  2. Background information about the country • 5.8 % secondary education, 1.1 % tertiary education (World Bank, 2001) • 120 tribes, many languages, official one Swahili and English • Although the statistics from 2002 say that there were 80,000 internet users the amount is already much higher. • The estimate is that 25 % of population can theoretically access the internet. (Geographically internet covers 7 %) • 270.0Gross national income ($) / per capita (World Bank, 2001), increasing

  3. National ICT policy 2003 • National ICT policy 2003 emphases: • human capital • local content • ICT leadership <= development of curricula and teaching/learning methods

  4. Local way or not? • Despite of globalization, all the countries have national cultural differences, also inside each country. The globalization of the culture is often like homogenization. Homogenization means that the western culture has a big influence on the other countries and cultures. The third view is cultural hybridization¸ which concentrates (Avgerou, 2002)

  5. Research Content and Group • We designed and organized an introductory course on ICT which concentrated on programming at Tumaini University, Iringa University College. Iringa University College is a ten-years-old higher education institution in southern highlands of Tanzania. • The participants of the programming course were 27 second-year teacher trainees in a bachelor’s program in mathematics and computer applications education. There were 11 females and 16 males. The average age of the participants was 35. Most of the students had experience teaching in secondary schools, average about 10 years. • Their previous experiences with using computers involved only the limited use of basic computer applications, like word processing or web browsing programs.

  6. What to find out? • Observiving the contextualization needs an d possiblilities of high standard ICT education • Analyzing the usefulness of concretizing, e.g. intelligent I-Blocks as a part of ICT education development • Developing ICT curriculum and ICT education with Tumaini University, Iringa University College, Tanzania

  7. What are I-Blocks? • Intelligent Building Blocks • LEGO DUPLO covered containing a microprocessor and communication channels • PIC16F876 40-pin 8 bit CMOS Flash micro controller • 4 serial two-way connections • energy transfer in corners and on studs • For ”programming by building” • The processing in the physical construction is distributed among all the building blocks

  8. This study We had introduction to programming course fall 2004, in which we applied these ideas. Possible usefulness of concretizing? Is there any difference between I-Block-groups and other ones? What the student have learnt or not?

  9. The schedule of the course

  10. Data collection during the course

  11. Results Table II. Paired t-test on the difference between the results of exercises of the final exam. Table I. e1b & e6b = standardized result of exercise 1 and 6 e2e5b = standardized average result of exercises 2-5 significance p: * p<0,05 almost meaningful, ** p< 0,01 meaningful, *** p<0,001 highly meaningful

  12. Results Table II. Paired t-test on the difference between the results of exercises of the final exam. e1b & e6b = standardized result of exercise 1 and 6 e2e5b = standardized average result of exercises 2-5 significance p: * p<0,05 almost meaningful, ** p< 0,01 meaningful, *** p<0,001 highly meaningful

  13. Results TABLE III. Four cluster model grouping the students according to the course results.

  14. Conclusion / Discussion • algorithmical exercises difficult • problem solving promising • concretizing might support weakest students • much to learn

  15. More information Educational Technology, Department of Computer Science,University of Joensuu, Finland http://cs.joensuu.fi/edtech Adaptrononics Group, Maersk Mc-Kinney Moller Institute, University of Southern Denmark http://www.adaptronics.dk/ Tumaini University, Iringa University Collage, Tanzania http://www.tumaini.ac.tz/

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