基于内外环反馈的高等教育统计智能辅导系统

Sietske Tacoma, P. Drijvers, J. Jeuring
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引用次数: 7

摘要

本文的同行评议历史可在https://publons.com/publon/10上获得。1111 / jcal.12491。摘要智能辅导系统(ITSs)可以提供任务内步骤的内环反馈和多任务执行情况的外环反馈。虽然研究通常分别处理这些反馈类型,但许多it同时提供它们。本研究旨在评估内外环结合反馈对社科学生在大学一年级统计学课程学习过程及成绩的影响。在521名参与者的2 × 2因子设计(精心设计的内环vs最小的内环和外环vs无外环反馈)中,通过多元线性回归模型评估了两种反馈类型及其组合的效果。结果显示,根据学生先前的知识和经验,效果好坏参半,对课程表现没有总体影响。在接受详尽的内环反馈时,学生倾向于较少使用外环反馈。因此,我们建议逐一引入反馈类型,并在相当长的一段时间内提供这些类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined inner and outer loop feedback in an intelligent tutoring system for statistics in higher education
Peer Review The peer review history for this article is available at https://publons.com/publon/10. 1111/jcal.12491. Abstract Intelligent tutoring systems (ITSs) can provide inner loop feedback about steps within tasks, and outer loop feedback about performance on multiple tasks. While research typically addresses these feedback types separately, many ITSs offer them simultaneously. This study evaluates the effects of providing combined inner and outer loop feedback on social sciences students' learning process and performance in a first-year university statistics course. In a 2 x 2 factorial design (elaborate inner loop vs. minimal inner loop and outer loop vs. no outer loop feedback) with 521 participants, the effects of both feedback types and their combination were assessed through multiple linear regression models. Results showed mixed effects, depending on students' prior knowledge and experience, and no overall effects on course performance. Students tended to use outer loop feedback less when also receiving elaborate inner loop feedback. We therefore recommend introducing feedback types one by one and offering them for substantial periods of time.
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