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Dr. A.Porshnev 2

ISCAR 20 11, 5 - 10 September. Do new media affect learning motivation: cross cultural study of German and Russian students? 1. Dr. A.Porshnev 2 National Research University – Higher School of Economics Nizhniy Novgorod , Russia Prof.Dr.H.Giest Potsdam University , German y.

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Dr. A.Porshnev 2

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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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