Instructor feedback based on writing subtask sequence patterns becomes problematic as the number of learners increases¶

Claim · All claims
Evidence · 1 study · design r2 · q1
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? Analyzing sequence patterns of writing subtasks for all learners manually becomes problematic as learner numbers increase, motivating automated estimation. → Uto 2020

Evidence¶

Uto 2020¶

Uto, M., Miyazawa, Y., Kato, Y., Nakajima, K., & Kuwata, H. (2020). Time- and Learner-Dependent Hidden Markov Model for Writing Process Analysis Using Keystroke Log Data. Int J Artif Intell Educ, 30, 271–298. https://doi.org/10.1007/s40593-019-00189-9

q1 · i? · design · r2

The article's motivation states that instructors' manual analysis of "sequence patterns for all learners" becomes problematic "as the number of learners increases," providing the rationale for the machine-learning method.

"For such feedback, instructors need to analyze sequence patterns for all learners, which becomes problematic as the number of learners increases."

Discussion¶

Related Claims¶

• Clustering yields a small number of behaviorally distinct team clusters that instructors can use for cluster-differentiated feedback — related
• The proposed model's effectiveness was demonstrated by applying it to actual keystroke log datasets — related