[论文解读] Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning

Mark Abdelshiheed, Zhou, Guojing+3 more|arXiv (Cornell University)|Mar 17, 2023

Innovative Teaching and Learning Methods参考文献 22被引用 7

一句话总结

论文研究元认知技能（策略意识和时间意识）与动机如何共同影响逻辑与概率 ITS 辅导中的学习并产生跨领域迁移，发现高动机结合两种元认知技能可带来最强的跨域迁移效果。

ABSTRACT

In this work, we investigate how two factors, metacognitive skills and motivation, would impact student learning across domains. More specifically, our primary goal is to identify the critical, yet robust, interaction patterns of these two factors that would contribute to students' performance in learning logic first and then their performance on a subsequent new domain, probability. We are concerned with two types of metacognitive skills: strategy-awareness and time-awareness, that is, which problem-solving strategy to use and when to use it. Our data were collected from 495 participants across three consecutive semesters, and our results show that the only students who consistently outperform their peers across both domains are those who are not only highly motivated but also strategy-aware and time-aware.

研究动机与目标

• Investigate how two metacognitive skills—strategy-awareness and time-awareness—influence learning within a logic domain and transfer to a probability domain.
• Examine how motivation interacts with these metacognitive skills to affect learning outcomes.
• Assess whether the interaction patterns predict preparation for future learning in a subsequent, different domain.

提出的方法

• Measure metacognitive skills from logic tutor interactions by coding strategy switches and timing of switches to compute MetaScore.
• Define MetaScore as: MetaScore_i = sum over levels and problems of [level * SAware_ip * TAware_ip], where SAware indicates strategy switch and TAware indicates early (<=30 actions) vs late (>30 actions) switches.
• Categorize students into Str_Time (both skills), Str Only (strategy-aware only), and Default (neither).
• Assess motivation using the initial two problems’ accuracy of rule applications to create HM vs LM groups per tutor.
• Normalize pre/posttest scores to [0,100] and compute normalized learning gain (NLG) as (post-pre)/sqrt(100-pre).
• Analyze effects via ANCOVA and ANOVA to test main and interaction effects of metacognition and motivation across two tutors: logic (FC/BC choices) and probability (BC only).

(a) Direct Proof

实验结果

研究问题

• RQ1 How do strategy-awareness and time-awareness individually and jointly affect learning within the logic tutor and transfer to the probability tutor?
• RQ2 How does motivation modulate the impact of these metacognitive skills on learning outcomes and preparation for future learning?
• RQ3 Do interaction patterns between metacognitive skills and motivation predict cross-domain performance more robustly than either factor alone?

主要发现

Tutor	Group	Size	Pre	Post	NLG
Logic	Str_Time	145	78.4 (3.2)	75.8 (1.7)	0.94 (0.395)
Logic	Str Only	166	74.9 (3)	68.2 (1.67)	-0.46 (0.39)
Logic	Default	184	75.5 (2.8)	70.9 (1.68)	0.19 (0.393)
Probability	Str_Time	145	72.3 (2.8)	75.5 (3)	0.02 (0.06)
Probability	Str Only	166	72.1 (2.5)	74 (2.8)	0.01 (0.05)
Probability	Default	184	71.8 (2.6)	73.4 (2.6)	-0.007 (0.05)

• Strategy-awareness alone does not guarantee better learning in logic; time-awareness is necessary for the observed gains.
• In the logic tutor, Str_Time learners outperform Str Only and Default in posttest and NLG, while no significant differences appear in the probability tutor by metacognitive group alone.
• Motivation independently improves posttest scores in both tutors; high-motivation groups show higher learning gains in probability.
• Across logic and probability, only the high-motivation, Str_Time group shows the strongest performance, indicating an aptitude-treatment interaction (ATI) where motivation gates the effectiveness of metacognitive skills.
• In the probability tutor, there is a significant interaction between metacognition and motivation for NLG, with Str_Time and Str Only outperforming Default among high-motivation students.
• Str_Time consistently yields superior outcomes among highly motivated students, suggesting time-awareness is crucial for consistent cross-domain preparation for future learning.

(b) Indirect Proof