期刊：
British Journal of Educational Technology,2024年55(5) ISSN：0007-1013
通讯作者：
Ba, S;Hu, X
作者机构：
[Ba, Shen] Educ Univ Hong Kong, Dept Curriculum & Instruct, Hong Kong, Peoples R China.;[Hu, Xiao] Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China.;[Stein, David] Ohio State Univ, Coll Educ & Human Ecol, Columbus, OH USA.;[Liu, Qingtang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Ba, Shen; Ba, S] Educ Univ Hong Kong, Dept Curriculum & Instruct, Tai Po, 10 Lo Ping Rd, Hong Kong, Peoples R China.
通讯机构：
[Ba, S ] E;[Hu, X ] U;Educ Univ Hong Kong, Dept Curriculum & Instruct, Tai Po, 10 Lo Ping Rd, Hong Kong, Peoples R China.;Univ Hong Kong, Fac Educ, Pokfulam, Room 209, Runme Shaw Bldg, Hong Kong, Peoples R China.
关键词：
community of inquiry;epistemic network analysis;learning analytics;online discussion;trajectory tracking
摘要：
<jats:title>Abstract</jats:title><jats:p>Accurate assessment and effective feedback are crucial for cultivating learners' abilities of collaborative problem‐solving and critical thinking in online inquiry‐based discussions. Based on quantitative content analysis (QCA), there has been a methodological evolvement from descriptive statistics to sequential mining and to network analysis for mining coded discourse data. Epistemic network analysis (ENA) has recently gained increasing recognition for modelling and visualizing the temporal characteristics of online discussions. However, due to methodological restraints, some valuable information regarding online discussion dynamics remains unexplained, including the directionality of connections between theoretical indicators and the trajectory of thinking development. Guided by the community of inquiry (CoI) model, this study extended generic ENA by incorporating directional connections and stanza‐based trajectory tracking. By examining the proposed extensions with discussion data of an online learning course, this study first verified that the extensions arecomparable with QCA, indicating acceptable assessment validity. Then, the directional ENA revealed that two‐way connections between CoI indicators could vary over time and across groups, reflecting different discussion strategies. Furthermore, trajectory tracking effectively detected and visualized the fine‐grained progression of thinking. At the end, we summarize several research and practical implications of the ENA extensions for assessing the learning process.<jats:boxed-text content-type="box" position="anchor"><jats:caption><jats:title>Practitioner notes</jats:title></jats:caption><jats:sec><jats:title>What is already known about this topic</jats:title><jats:p>
<jats:list list-type="bullet">
<jats:list-item><jats:p>Assessment and feedback are crucial for cultivating collaborative problem‐solving and critical thinking in online inquiry‐based discussions.</jats:p></jats:list-item>
<jats:list-item><jats:p>Cognitive presence is an important construct describing the progression of thinking in online inquiry‐based discussions.</jats:p></jats:list-item>
<jats:list-item><jats:p>Epistemic network analysis is gaining increasing recognition for modelling the temporal characteristics of online inquiries.</jats:p></jats:list-item>
</jats:list></jats:p></jats:sec><jats:sec><jats:title>What this paper adds</jats:title><jats:p>
<jats:list list-type="bullet">
<jats:list-item><jats:p>Directional connections between discourses can reflect different online discussion strategies of groups and individuals.</jats:p></jats:list-item>
<jats:list-item><jats:p>A pair of connected discourses coded with the community of inquiry model can have different meanings depending on their temporal order.</jats:p></jats:list-item>
<jats:list-item><jats:p>A trajectory tracking approach can uncover the fine‐grained progression of thinking in online inquiry‐based discussions.</jats:p></jats:list-item>
</jats:list></jats:p></jats:sec><jats:sec><jats:title>Implications for practice and/or policy</jats:title><jats:p>
<jats:list list-type="bullet">
<jats:list-item><jats:p>Besides the occurrences of individual discourses, examining the meanings of directional co‐occurrences of discourses in online discussions is worthwhile.</jats:p></jats:list-item>
<jats:list-item><jats:p>Groups and individuals can employ different discussion strategies and follow diverse paths to thought development.</jats:p></jats:list-item>
<jats:list-item><jats:p>Developmental assessment is crucial for understanding how participants achieve specific outcomes and providing adaptive feedback.</jats:p></jats:list-item>
</jats:list></jats:p></jats:sec></jats:boxed-text></jats:p>
摘要：
Abstract This research employs the fuzzy‐set qualitative comparative analysis (fsQCA) method to investigate the configurations of multiple factors influencing scientific concept learning, including augmented reality (AR) technology, the concept map (CM) strategy and individual differences (eg, prior knowledge, experience and attitudes). A quasi‐experiment was conducted with 194 seventh‐grade students divided into four groups: AR and CM (N = 52), AR and non‐CM (N = 51), non‐AR and CM (N = 40), non‐AR and non‐CM (N = 51). These students participated in a science lesson on ‘The structure of peach blossom’. This study represents students' science learning outcomes by measuring their academic performance and cognitive load. The fsQCA results reveal that: (1) factors influencing students' academic performance and cognitive load are interdependent, and a single factor cannot constitute a necessary condition for learning outcomes; (2) multiple pathways can lead to the same learning outcome, challenging the notion of a singular best path derived from traditional analysis methods; (3) the configurations of good and poor learning outcomes exhibit asymmetry. For example, high prior knowledge exists in both configurations leading to good and poor learning outcomes, depending on how other conditions are combined. Practitioner notes What is already known about this topic Augmented reality proves to be a useful technological tool for improving science learning. The concept map can guide students to describe the relationships between concepts and make a connection between new knowledge and existing knowledge structures. Individual differences have been emphasized as essential external factors in controlling the effectiveness of learning. What this paper adds This study innovatively employed the fsQCA analysis method to reveal the complex phenomenon of the scientific concept learning process at a fine‐grained level. This study discussed how individual differences interact with AR and concept map strategy to influence scientific concept learning. Implications for practice and/or policy No single factor present or absent is necessary for learning outcomes, but the combinations of AR and concept map strategy always obtain satisfactory learning outcomes. There are multiple pathways to achieving good learning outcomes rather than a single optimal solution. The implementation of educational interventions should fully consider students' individual differences, such as prior knowledge, experience and attitudes.
期刊：
Education and Information Technologies,2023年29(5):6319-6340 ISSN：1360-2357
通讯作者：
Yu, Shufan;Liu, QT
作者机构：
[Ma, Jingjing; Liu, Qingtang; Liu, Jiaxu; Yu, Shufan] Cent China Normal Univ, Fac Artificial Intelligence Educ, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Ma, Jingjing; Liu, Qingtang; Liu, Jiaxu; Yu, Shufan] Cent China Normal Univ, Hubei Res Ctr Educ Informationizat, Wuhan, Peoples R China.;[Yang, Yuanyuan] Shuanglin primary Sch, Chengdu, Sichuan, Peoples R China.;[Yu, Shufan; Liu, Qingtang] Cent China Normal Univ, Fac Artificial Intelligence Educ, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Yu, Shufan; Liu, Qingtang] Cent China Normal Univ, Hubei Res Ctr Educ Informationizat, Wuhan, Peoples R China.
通讯机构：
[Yu, SF; Liu, QT ] ;Cent China Normal Univ, Fac Artificial Intelligence Educ, Sch Educ Informat Technol, Wuhan, Peoples R China.;Cent China Normal Univ, Hubei Res Ctr Educ Informationizat, Wuhan, Peoples R China.
作者：
Jiaojiao Wang;Kui Xie*;Qingtang Liu;Taotao Long;Guoqing Lu
期刊：
Journal of Computers in Education,2023年10(2):217-235 ISSN：2197-9987
通讯作者：
Kui Xie
作者机构：
[Jiaojiao Wang; Qingtang Liu; Taotao Long; Guoqing Lu] School of Educational Information Technology, Central China Normal University, Wuhan, China;[Kui Xie] Department of Educational Studies, College of Education and Human Ecology, The Ohio State University, Columbus, USA
通讯机构：
[Kui Xie] D;Department of Educational Studies, College of Education and Human Ecology, The Ohio State University, Columbus, USA
作者机构：
[Ma, Jingjing; Han, Miaomiao; Liu, Qingtang; Yu, Shufan; Wu, Linjing] Cent China Normal Univ, Fac Artificial Intelligence Educ, Sch Educ Informat Technol, Wuhan 430079, Hubei, Peoples R China.;[Ma, Jingjing; Han, Miaomiao; Liu, Qingtang; Yu, Shufan; Wu, Linjing] Cent China Normal Univ, Hubei Res Ctr Educ Informationizat, Wuhan 430079, Hubei, Peoples R China.;[Johnson-Glenberg, Mina C.] Arizona State Univ, Dept Psychol, Tempe, AZ 85281 USA.;[Ba, Shen] Univ Hong Kong, Fac Educ, Hong Kong 999077, Peoples R China.
通讯机构：
[Shufan Yu; Qingtang Liu] S;School of Educational Information Technology, Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, 430079, Hubei, China<&wdkj&>Hubei Research Center for Educational Informationization, Central China Normal University, 430079, Hubei, China
关键词：
Augmented and virtual reality;Applications in subject areas;Human-computer interface;Media in education;Simulations
期刊：
Journal of Science Education and Technology,2023年32(2):153-167 ISSN：1059-0145
通讯作者：
Jingjing Ma
作者机构：
[Ma, Jingjing; Liu, Qingtang; Yu, Shufan] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Ma, Jingjing; Liu, Qingtang; Yu, Shufan] Cent China Normal Univ, Hubei Res Ctr Educ Informationizat, Wuhan, Peoples R China.;[Wang, Qiyun] Nanyang Technol Univ, Natl Inst Educ, Learning Sci & Technol Acad Grp, Singapore, Singapore.;[Xu, Suxiao] Hangzhou Jialvyuan Primary Sch, Hangzhou, Peoples R China.
通讯机构：
[Jingjing Ma] S;School of Educational Information Technology, Central China Normal University, Wuhan, People’s Republic of China<&wdkj&>Hubei Research Center for Educational Informationization, Central China Normal University, Wuhan, People’s Republic of China
关键词：
Augmented reality;Microscopic composition of substances;Learning motivation;Technology perception;Chemistry education
作者机构：
[Ma, Jingjing; Ba, Shen; Liu, Qingtang; Yu, Shufan] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Ma, Jingjing; Ba, Shen; Liu, Qingtang; Yu, Shufan] Cent China Normal Univ, Hubei Res Ctr Educ Informationizat, Wuhan, Peoples R China.;[Le, Huixiao] Peking Univ, Grad Sch Educ, Beijing, Peoples R China.
通讯机构：
[Qingtang Liu] S;School of Educational Information Technology, Central China Normal University, Wuhan, People’s Republic of China<&wdkj&>Hubei Research Center for Educational Informationization, Central China Normal University, Wuhan, People’s Republic of China
作者机构：
[Lu, Guoqing; Liu, Qingtang] Cent China Normal Univ, Sch Educ Informat Technol, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.;[Xie, Kui] Ohio State Univ, Coll Educ & Human Ecol, 29 Woodruff Ave,322A Ramseyer Hall, Columbus, OH 43210 USA.
通讯机构：
[Guoqing Lu; Guoqing Lu Guoqing Lu Guoqing Lu] S;[Kui Xie; Kui Xie Kui Xie Kui Xie] C;College of Education and Human Ecology, The Ohio State University, Columbus, Ohio, USA<&wdkj&>School of Educational Information Technology, Central China Normal University, Wuhan, China
关键词：
academic motivation;experience sampling method;hierarchical linear modelling;perceived support;situational engagement;smart classroom
