[论文解读] Preparing Unprepared Students For Future Learning
研究表明：通过带有示例和提示的显式 BC（后向推理）策略教学，能够帮助记忆型（Rote）和好学者型（Dabbler）学生在逻辑与概率领域赶上选择型（Selective）学习者，且效应在六周后仍持续。
Based on strategy-awareness (knowing which problem-solving strategy to use) and time-awareness (knowing when to use it), students are categorized into Rote (neither type of awareness), Dabbler (strategy-aware only) or Selective (both types of awareness). It was shown that Selective is often significantly more prepared for future learning than Rote and Dabbler (Abdelshiheed et al., 2020). In this work, we explore the impact of explicit strategy instruction on Rote and Dabbler students across two domains: logic and probability. During the logic instruction, our logic tutor handles both Forward-Chaining (FC) and Backward-Chaining (BC) strategies, with FC being the default; the Experimental condition is taught how to use BC via worked examples and when to use it via prompts. Six weeks later, all students are trained on a probability tutor that supports BC only. Our results show that Experimental significantly outperforms Control in both domains, and Experimental Rote catches up with Selective.
研究动机与目标
- Investigate whether explicit instruction on when to use a problem-solving strategy improves learners with low strategy awareness.
- Examine the impact of strategy-awareness plus time-awareness training on performance in two deductive domains (logic and probability).
- Assess whether Rote and Dabbler groups can close the gap with Selective learners after intervention.
- Analyze long-term effects (six weeks later) in a different domain using a second tutor.
- Characterize strategy-switch behaviors before and after training to understand metacognitive changes.
提出的方法
- Two ITS tutors were used: a logic tutor supporting Forward-Chaining (FC) and Backward-Chaining (BC) with BC taught explicitly via worked examples and prompts; a probability tutor supporting BC only.
- Experimental group received BC worked examples and prompts to switch when appropriate; Control group received no strategy instruction.
- Participants were CS undergraduates at NC State; metacognitive groups were predicted by a random-forest classifier based on pretest solving patterns; groups: Rote Exp, Dabbler Exp, Rote Ctrl, Dabbler Ctrl, Selective.
- Six weeks after logic training, all participants trained on a probability tutor and posttested.
- Outcomes included pretest/posttest scores, isomorphic posttests, normalized learning gain (NLG), and strategy-switch metrics.
- Statistical analyses included ANOVAs and ANCOVAs with pretest scores as covariates to assess condition and metacognitive group effects.
实验结果
研究问题
- RQ1Can explicit BC strategy instruction with worked examples and time-based prompts improve learning for Rote and Dabbler students in deductive domains?
- RQ2Do improvements from the logic domain transfer to a subsequent probability domain after a six-week interval?
- RQ3Do Rote students benefit more than Dabbler or Selective students from the intervention?
- RQ4Does the intervention enable Rote and Dabbler groups to catch up to Selective learners across domains?
- RQ5What are the observed strategy-switch behaviors (early/late) associated with the intervention?
主要发现
- Experimental learners significantly outperformed Control in both logic and probability domains.
- Rote students receiving the intervention benefited the most, with posttest and NLG improvements approaching or matching Selective learners.
- Dabbler learners showed gains in logic posttest and probability posttest but with more nuance across measures.
- The six-week transfer to probability showed sustained advantages for Experimental groups over Control.
- Strategy-switch analysis indicated Experimental Rote matched Selective in early switching during training and posttest, suggesting successful metacognitive alignment.
- Selective learners generally outperformed Controls, and Experimental Rote sometimes exceeded Selective on logic posttests.
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