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The Impact of New Media on Learning Motivation: A Comparative Study of German and Russian Students

This study explores how new media affects learning motivation among university students in Germany and Russia. Supported by the Alexander von Humboldt Foundation, it investigates the potential benefits and challenges of technology in education, using a cross-cultural approach. Through surveys and questionnaires, researchers examine intrinsic and extrinsic motivation, web usage, and the impact of social networks like Facebook and communication tools like Skype. The findings reveal trends in Internet penetration, technology adoption, and the correlation with students' learning behaviors in both countries.

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The Impact of New Media on Learning Motivation: A Comparative Study of German and Russian Students

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  1. ISCAR 2011, 5-10 September Do new media affect learning motivation: cross cultural study of German and Russian students?1 Dr. A.Porshnev2 National Research University – Higher School of Economics Nizhniy Novgorod, Russia Prof.Dr.H.Giest Potsdam University, Germany 1 Project was supported by Alexander von Humboldt Foundation grant 3.1-RUS/1130038 BUKA 2 Porshnev’s research was supported by Scientific Foundation of State University Higher School of Economics Moscow grants: # 07-01-160, #10-01-0021 and travel grant to participate in ISCAR2011

  2. Students and new technologies • New learning opportunities (Wiki, Communities of Practice and etc.) • Learning neutral changes (Social networks – Facebook, Communication – Skype and etc.) • Potential traps (Copy Paste – Plagiarism, Information overload)

  3. Zero Hypothesis: Penetration of Internet in society and opportunities Internet create increase intrinsic learning motivation of students Internet world statistics • Internet penetration: 67.0% Germanу (Dec/08, per Nielsen) - 27.0% Russia (Dec/08, 27, per POF) In our survey • Technology in University (Germany - Russia) • Time of computer ownership (Germany - Russia) • Frequency of computer usage (Germany - Russia)

  4. Question: I copy and paste texts from a books or Internet uncited?(Russian sample, data from our research) In Russia sum 51,8%

  5. Methods Russian - German – Russian blind back translated questionnaire (84 questions) • Demographic questions • Questions about students’ behavior • Motivationscales • based on • “Motivated Strategies for Learning Questionnaire” (P.Pintrich 1991); • “Motivation of Internet Users in Russia” (A.Voiskunsky and others 2000); • “Students Motivation of usage Internet in Russia” (A.Porshnev, 2008); • “Pew Internet & American Life Project” (2009); • “Classroom Technology in Business Schools” (B.Parker, D.Burnie, 2009); Sections of questionnaire

  6. Geography of research Russia - 865 (1119) students Germany - 332 (523) students

  7. Motivation scales • Intrinsic orientations * • Extrinsic orientations * • Test Anxiety * • Web-usage in studying *Modified scales from Motivated Strategies for Learning Questionnaire were used (MSLQ, P.Pintrich et al. 1991)

  8. Intrinsic motivation scale(8 questions) Example of items • I prefer course material that really challenges me so I can learn new things.(MSLQ) • There are courses I am so interested in, that I continue studying even if I have to work more than necessary (for example, participate in research groups) (created) α-CronbachRussia = 0,733 α-CronbachGermany = 0,733

  9. Test Anxiety scale(4 questions) Example of items • When I take a test I think about how poorly I am doing compared with other students(MSLQ) • When I take tests I think of the consequences of failing(MSLQ) α-CronbachRussia = 0,68, α-CronbachGermany = 0,73

  10. Extrinsic motivation scale (5 questions) Example of items • Getting a good grade is the most satisfying thing for me right now (MSLQ) • I make the tasks, because otherwise I will have troubles (created) α-CronbachRussia= 0,658, α-CronbachGermany= 0,620

  11. Web-usage in studying scale(6 questions) Example of items • I share my works in Internet (in the blog, site or forum), because I want to receive feedback(created) • During the course I used to discuss the materials on-line(created) α-CronbachRussia= 0,726, α-CronbachGermany= 0,775

  12. Web-usage in studying scale(6 questions) Example of items • I share my works in Internet (in the blog, site or forum), because I want to receive feedback(created) • During the course I used to discuss the materials on-line(created) α-CronbachRussia= 0,726, α-CronbachGermany= 0,775

  13. Could we compare data? • Blind back-translation method (Beck et al., 2003): Russian – German - Russian • Sample equivalence (control for university level, specialization field, age, gender) • Scale equivalence Structural equation modeling (made in EQS) • COVS analysis • MACS analysis

  14. Structural analysis 4Factor model (INT, EXT, TA, A_Web) - low fit for data More detailed model

  15. Intrinsic motivation Subscale 1: Engagement mb2 There are courses I am so interested in, that I continue studying even if I have to work more than necessary (for example, participate in research groups) mb3 Some of task provide me such a pleasure from using my creativity, that I want to spent more time doing them than it is necessary for the exam.

  16. Intrinsic motivation subscale 2 – Choice mb1*. I prefer course material that really challenges me so I can learn new things mb25 During my studying in University I became so interested in one or several subjects that it influences my choice of the future professional activities.

  17. Intrinsic motivation Subscale 3: Challenge mb24* When I have the opportunity in this class, I choose course assignments that I can learn from even if they don't guarantee a good grade. mb16 If I have a choice between creative exercise and formal one I prefer the creative, even if it could be more complicated

  18. Results of covariance structure analysis 8FACTOR model with partial structural invariance Intrinsic motivation 3 Web activity 3 Test anxiety 2 - Configural invariance No • Metric invariance • Scalar invariance • Invariance of factor variance • Invariance of latent means

  19. invariance structure found: • Intrinsic motivation - F1(engagement), F2(choice), F3(challenge) • Test Anxiety – F4(exams), F5(nervous state) • Configural invariance • Metric invariance • Scalar invariance • Invariance of factor variance • Invariance of latent means • Results of simultaneous multigroupanalysis FIT INDICES (BASED ON MODIFIED INDEPENDENCE MODEL, AND ----------- BASED ON COVARIANCE MATRIX ONLY, NOT THE MEANS) BENTLER-BONETT NORMED FIT INDEX = .962 BENTLER-BONETT NON-NORMED FIT INDEX = .988 COMPARATIVE FIT INDEX (CFI) = .992 BOLLEN'S (IFI) FIT INDEX = .992 MCDONALD'S (MFI) FIT INDEX = .993 ROOT MEAN-SQUARE ERROR OF APPROXIMATION (RMSEA) = .021 90% CONFIDENCE INTERVAL OF RMSEA ( .000, .034) EQS output:

  20. Significant differences Intrinsic motivation • F1(intrinsic engagement)  Russia • F2(intrinsic trajectory choice)  Germany • F3(intrinsic challenge)  Russia Test Anxiety • F4 (exams failing anxiety)  Germany • F5(nervous state while test or exams)  Germany

  21. Differences Question: What for you used the computer yesterday?

  22. Similarities

  23. Question “Do you feel overloaded with information from different sources?”. Differences

  24. Differences Question: I copy and paste texts from a books or Internet uncited?

  25. Conclusion • ICT have no global influence on learning motivation • Students require not only ICT tools or instruments, but also psychological tool to cope with this instruments. “We should give a child instrument (tool), which would play a special role – organization of his own behavior” (L.Vygotsky, 1930) • A new challenge …

  26. Dr. A.Porshnev National Research University – Higher School of Economics Nizhniy Novgorod,Russia Dr.Prof.H.Giest Potsdam University, Germany aporshnev@hse.ru giest@uni-potsdam.de Thank you for your attention

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