Journals / Turkish Online Journal of Distance Education / 2019 / Cilt: 20 - Sayı: 2

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

Pages
21–45
Publication Date
2019-04-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These findings revealed that study time is indicative of problematic students that could be targets for interventions.

📌 3 Key Takeaways

🎯
Objective & Hypothesis: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.
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Key Findings & Data: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.
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Conclusion & Impact:These findings revealed that study time is indicative of problematic students that could be targets for interventions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Distance training · student characteristics · self-regulated learning

Abstract

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.

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Cite This Article

STILLER, K. D., BACHMAIER, R. (2019). Using Study Times for Identifying Types of Learners in a Distance Training for Trainee Teachers. Turkish Online Journal of Distance Education, Cilt: 20 - Sayı: 2, 21–45. https://ajindex.com/articles/140264

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