摘要：
Despite the continuous emphasis on emotion in multimedia learning, it was still unclear how pedagogical agent emotional cues might affect learning. In the present study, a between-subjects experiment was performed to examine the effects of a pedagogical agent with dual-channel emotional cues on learners' emotions, cognitive load, and knowledge transfer performance. Participants from a central Chinese university (age mean = 21.26, N = 66) were randomly divided into three groups. These groups received instructions from an affective pedagogical agent, a neutral pedagogical agent, or a neutral voice narration without pedagogical agent embodiment. Results showed that learners assigned the affective pedagogical agent reported a significantly higher emotional level than learners assigned the neutral pedagogical agent. Learners' perceived task difficulty was not significantly different among groups while instructional efficiency was significantly higher for learners with the affective pedagogical agent. Moreover, learners assigned to the affective pedagogical agent performed significantly better on the knowledge transfer test than those assigned the neutral pedagogical agent or the neutral voice.
作者机构：
[Liu, Qingtang; Wu, Linjing] School of Educational Information Technology, Central China Normal University, China;Information Systems and Technology, The University of Dodoma, Tanzania, United Republic of;[Swai, Carina Titus] School of Educational Information Technology, Central China Normal University, China<&wdkj&>Information Systems and Technology, The University of Dodoma, Tanzania, United Republic of
会议名称：
13th International Conference on Education Technology and Computers, ICETC 2021
作者机构：
Authors to whom correspondence should be addressed.;School of Information Technology in Education, South China Normal University, Guangzhou 510631, China;[Qingtang Liu; Linjing Wu] School of Educational Information Technology, Central China Normal University, Wuhan 430079, China;[Yunxiang Zheng; Jingxiu Huang] Authors to whom correspondence should be addressed.<&wdkj&>School of Information Technology in Education, South China Normal University, Guangzhou 510631, China
通讯机构：
[Yunxiang Zheng; Jingxiu Huang] A;Authors to whom correspondence should be addressed.<&wdkj&>School of Information Technology in Education, South China Normal University, Guangzhou 510631, China
关键词：
comma disambiguation;feature engineering;hyperparameter tuning;imbalanced learning;natural language understanding;random forests
摘要：
Natural language understanding technologies play an essential role in automatically solving math word problems. In the process of machine understanding Chinese math word problems, comma disambiguation, which is associated with a class imbalance binary learning problem, is addressed as a valuable instrument to transform the problem statement of math word problems into structured representation. Aiming to resolve this problem, we employed the synthetic minority oversampling technique (SMOTE) and random forests to comma classification after their hyperparameters were jointly optimized. We propose a strict measure to evaluate the performance of deployed comma classification models on comma disambiguation in math word problems. To verify the effectiveness of random forest classifiers with SMOTE on comma disambiguation, we conducted two-stage experiments on two datasets with a collection of evaluation measures. Experimental results showed that random forest classifiers were significantly superior to baseline methods in Chinese comma disambiguation. The SMOTE algorithm with optimized hyperparameter settings based on the categorical distribution of different datasets is preferable, instead of with its default values. For practitioners, we suggest that hyperparameters of a classification models be optimized again after parameter settings of SMOTE have been changed.
期刊：
Journal of Educational Computing Research,2021年59(7):1319 - 1342 ISSN：0735-6331
通讯作者：
Wu, Linjing;Liu, Qingtang
作者机构：
[Wu, Linjing; Liu, Qingtang; Li, Jing; Yang, Weiqing; He, Liming; Zhang, Yaosheng] Cent China Normal Univ, Sch Educ Informat Technol, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.;[Liu, Qingtang] Cent China Normal Univ, Hubei Res Ctr Educ Informationizat, Wuhan, Hubei, Peoples R China.;[Cheng, Yun] Huang Gang Normal Univ, Sch Educ, Huanggang, Hubei, Peoples R China.
通讯机构：
[Wu, LJ; Liu, QT] C;Cent China Normal Univ, Sch Educ Informat Technol, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.
关键词：
collaborative knowledge building;knowledge contribution;information theory;amount of information;information gain
摘要：
The measurement of knowledge contribution in collaborative knowledge building is an important research topic in computer-supported collaborative learning. The information measures of knowledge contribution based on information theory are proposed in this study, which includes two measures: amount of information and information gain. Discourse data collected from a collaborative knowledge building activity were analyzed to validate these measures. The results showed that our information measures can complement the traditional behavioral. With the help of the two measures, community-level variation tendency and individual-level knowledge contribution characteristics could be analyzed in collaborative knowledge building activities. A log function was used to fit the community knowledge variation tendency to measure the convergence of knowledge building. Students were clustered into five types according to their behaviors and contributions in collaborative knowledge building. Both teachers and researchers can benefit from these two information measures by using them in practice.
摘要：
Metacognition is important in self-regulated learning and understanding its epistemic network can improve teaching and learning. We collected self-reported metacognition reflections on collaborative learning activities from 87 college students to analyze how students' metacognitive patterns differ by performance level and discipline type. We used an epistemic network analysis to identify these differences, and the results indicated that description of goals appeared most in self-reported reflections. There are variations in metacognitive patterns between different groups. High-score students had stronger connections around actions, while low-score students had stronger connections between metacognitive knowledge and context. The natural science students focused more on metacognitive knowledge and actions, while the humanities science students focused more on metacognitive experience and context. This implies that teachers should provide clear explanations about the collaborative learning goal, and a group strategy that takes both performance and discipline types into consideration could address the variation in metacognitive patterns.
摘要：
This study analysed the instructors' teaching presence of three courses conducted by an instructor to explore the effects of the instructors' online teaching presence on students' interactions and collaborative knowledge constructions. Content analysis, social network analysis, and lag sequential analysis were used to explore the mechanism of teaching presence on students' interactions and collaborative knowledge construction. Results demonstrate that the design and organization, as well as facilitating discourse, can facilitate students' interaction, reduce the number of peripheral students, and facilitate students' collaborative knowledge construction, especially in the knowledge sharing, discovery, discussion, and application, whereas direct instruction has positive effects on teachers' centrality and negative effects on knowledge negotiation and testing. The result can give the instructors some guidance on online teaching practices.
What is already known about this topic
What this paper adds
摘要：
This study investigates the role of a collaboration script, the Funnel Model, in supporting students’ computer-supported collaborative scientific argumentation, and how the students appropriated the collaboration script in scientific argumentation. In this exploratory case study, a class of 33 Secondary grade four students went through four phases of computer-supported collaborative argumentation activity scripted by the Funnel Model: individual ideation, intra-group synergy, inter-group critique and intra-group refinement. Multiple sources of data were collected including student-generated artefacts online at different phases of collaboration, and the post-intervention interviews with the students. The results show that the Funnel Model facilitated students’ computer-supported collaborative argumentation. The students’ levels of content mastery, motivation, classroom culture and time allocated for classroom participation affect students’ appropriation of the script for effective collaborative argumentation.
