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Using Study Times for Identifying Types of Learners in a Distance Training for Trainee Teachers

Yıl 2019, Cilt: 20 Sayı: 2, 21 - 45, 01.04.2019
https://doi.org/10.17718/tojde.557728

Öz

One focus of distance learning research is to explore the extent that learner characteristics and skills determine learning outcomes and to elaborate predictive models of performance. Modern approaches can benefit from objective data, such as various time indices and frequencies of learner actions, provided by log systems catching online traces to identify learners that are in threat of performance loss. This approach might result in better online diagnostics and intervention methods when the mechanisms behind log data are known. Following this idea, the current study gained objective and subjective study time parameters and explored how study time is connected to learner characteristics and learning by using a script-based modularized distance-training course about media education. Data was collected from 379 trainee teachers. Given a calculated workload of 60-90 min per training module, students were clustered into two groups: learners having spent less than 25 min for at least one of their completed modules (n = 118; short study time group) and learners having spent more than 25 min for each completed module (n = 261; long study time group). The first goal was to investigate the extent that study time is relevant for learning process and success. Groups were compared in their ratings of content difficulty, difficulty of studying, invested effort, and experienced pressure while learning, and their test performance. Differences between groups were found in all variables. The long study time learners experienced less content difficulty, studying difficulty, and pressure while learning, but reported more effort and showed higher performance. The second goal was to explore the effect of learner characteristics on study time. Groups were compared in their domain-specific prior knowledge, intrinsic motivation, computer attitude, computer anxiety, and use of learning strategies. Long study time learners showed a higher level of motivation, competences in metacognitive learning strategies, and strategy use for arranging an adequate learning environment. These findings revealed that study time is indicative of problematic students that could be targets for interventions.

Kaynakça

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Yıl 2019, Cilt: 20 Sayı: 2, 21 - 45, 01.04.2019
https://doi.org/10.17718/tojde.557728

Öz

Kaynakça

  • Agustiani, H., Cahyad, S., & Musa, M. (2016). Self-efficacy and self-regulated learning as predictors of students’ academic performance. The Open Psychology Journal, 9, 1-6. doi: 10.2174/1874350101609010001
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  • Akcapinar, G. (2016). Predicting students’ approaches to learning based on Moodle log. In L. Gómez Chova, A. López Martínez & I. Candel Torres (Eds.), EDULEARN16 Proceedings. 8th International Conference on Education and New Learning Technologies July 4th-6th, 2016 - Barcelona, Spain (pp. 2347-2352). doi: 10.21125/edulearn.2016.1473
  • Akcapinar, G., Altun, A., & Aşkar, P. (2015). Modeling Students’ Academic Performance Based on Their Interactions in an Online Learning Environment. Elementary Education Online, 14(3), 815-824. doi: 10.17051/io.2015.03160
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  • Schwartz, N. H., Andersen, C., Hong, N., Howard, B., & McGee, S. (2004). The influence of metacognitive skills on learner’s memory of information in a hypermedia environment. Journal of Educational Computing Research, 31, 77-93. doi: 10.2190/JE7W-VL6W-RNYF-RD4M
  • Shin, N., & Kim, J. (1999). An exploration of learner progress and drop-out in Korea National Open University. Distance Education, 20(1), 81-95. doi: 10.1080/0158791990200107
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  • Stiller, K. D. (in press). Fostering learning via pictorial access to on-screen text. Journal of Educational Multimedia and Hypermedia.
  • Stiller, K. D., & Bachmaier, R. (2017a). Dropout in an online training for in-service teachers. In A. Volungeviciene & A. Szűcs (Eds.), EDEN 2017 Annual Conference. Diversity matters! Conference proceedings (pp. 177-185). Budapest, Hungary: European Distance and E-Learning Network (EDEN).
  • Stiller, K. D., & Bachmaier, R. (2017b). Dropout in an online training for trainee teachers. European Journal of Open, Distance and E-Learning, 20(1), 80-95. doi: 10.1515/eurodl-2017-0005
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  • Tsai, C. W. (2011b). Achieving effective learning effects in the blended course: A combined approach of online self-regulated learning and collaborative learning with initiation. Cyberpsychology, Behavior, and Social Networking, 14(9), 505-510. doi: 10.1089/cyber.2010.0388
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  • Weinstein, C. E., & Palmer, D. R. (1990). Learning and study strategies inventory high school. Florida, US: H & H Publishing Company.
  • Wild, K.-P., & Schiefele, U. (1994). Lernstrategien im Studium: Ergebnisse zur Faktorenstruktur und Reliabilität eines neuen Fragebogens [Learning strategies of university students: Factor structure and reliability of a new questionnaire]. Zeitschrift für Differentielle und Diagnostische Psychologie, 15, 185-200.
  • Wladis, C., Hachey, A. C., & Conway, K. M. (2014). The representation of minority, female, and nontraditional STEM majors in the online environment at community colleges: A nationally representative study. Community College Review, 43, 142-164. doi: 10.1177/0091552114555904
  • Wong, S. L., Ibrahim, N., & Ayub, A. F. M. (2012). Learning strategies as correlates of computer attitudes: A case study among Malaysian secondary school students. International Journal of Social Science and Humanity, 2, 123-126. doi: 10.7763/IJSSH.2012.V2.80
  • Yukselturk, E., & Bulut, S. (2007). Predictors for student success in an online course. Educational Technology & Society, 10(2), 71-83.
  • Yurdugül, H., & Menzi Cetin, N. (2015). Investigation of the relationship between learning process and learning outcomes in e-learning environments. Eurasian Journal of Educational Research, 59, 57-74. doi: 10.14689/ejer.2015.59.4
  • Zimmerman, B. J., & Martinez-Pons, M. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American Educational Research Journal, 23, 614-628. doi: 10.3102/00028312023004614
  • Zimmerman, B. J., & Schunk, D. H. (Eds.). (2001). Self-regulated learning and academic achievement: Theoretical perspectives. Hillsdale, NJ: Erlbaum.
Toplam 97 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Klaus D. Stıller Bu kişi benim 0000-0002-9636-4516

Regine Bachmaıer Bu kişi benim 0000-0002-3479-5759

Yayımlanma Tarihi 1 Nisan 2019
Gönderilme Tarihi 30 Nisan 2018
Yayımlandığı Sayı Yıl 2019 Cilt: 20 Sayı: 2

Kaynak Göster

APA Stıller, K. D., & Bachmaıer, R. (2019). Using Study Times for Identifying Types of Learners in a Distance Training for Trainee Teachers. Turkish Online Journal of Distance Education, 20(2), 21-45. https://doi.org/10.17718/tojde.557728