學術資源整合系統-相關推薦
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| 作者 | Lin, H.-C. K.;Tsai, M.-C.; Tao-Hua Wang;Lu, W.-Y. |
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| 出版日期 | 2024 |
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| 著作名稱 | Application of WSQ (Watch-Summary-Question) flipped teaching in affective conversational robots: Impacts on learning emotion, self-directed learning, and learning effectiveness of senior high school students
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| 刊名 | International Journal of Human-Computer Interaction. |
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| 卷 | 13 |
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| 期 | 13 |
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| 關鍵字 | Dialogue robot; WSQ; learning emotions; selfregulated learning; |
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| 摘要 | The study constructed a self-directed learning system with digital art teaching materials by using
an affective conversational robot and a learning method guided by watch-summary-question
(hereinafter referred to as WSQ) worksheets. The objective of this study, the affective conversational
robot was used for interactive purpose and the WSQ learning strategy was integrated as
the self-directed learning framework in order to boost the motives for self-directed learning in the
students and also to help the teacher know students’ learning and difficulties. The EDRDA system
was developed based on the rapid application development (RAD), to make the affective conversational
robot enable to detect emotions and give appropriate feedback, we have compiled 4,200
sets of conversations to strengthen the training of Dialogflow intentions, and divided the conversations
into two kinds: course knowledge texts (digital art course related) and sentimental texts
(sentiment category). Subjects were 190 students from some senior high school in the southern
part of Taiwan and lasted for 8 weeks in total. For the sake of consistency, the study did not distinguish
between genders. There were 6 groups, with each group consisting of 4–5 randomized
students. Then, the odd groups were set to be control groups (CGs, N¼95), the affective selfdirected
learning system was integrated with the general worksheet and the even groups were
experiment groups (EGs, N¼95), the affective self-directed learning system was integrated with
the WSQ worksheet while. Students in both groups were compared against one another in their
differences in “learning emotions,” “positive learning emotions,” “negative learning emotions,”
“learning effectiveness,” “satisfaction with self-directed learning” and “self-directed learning method.”
The statistical quantitative analysis methods applied included analysis of covariance
(ANCOVA), independent sample t-test, linear regression, and Welch’s-test. Statistical results show
that the experiment group scored higher in positive learning emotions such as “hope” (LE ¼
2.05���, SL ¼ 0.18��), “enjoyment” (LE ¼ 1.91��, SL ¼ 0.20�), and “pride” (LE ¼ 1.59��, SL ¼
0.18���) in “learning effectiveness (LE)” and in “satisfaction with self-directed learning (SL)” than
the control group and lower in negative learning emotions such as “anxiety” (LE ¼ –0.99���, SL ¼
–0.30�) and “anger” (LE ¼ –0.86�, SL ¼ –0.20��). The study data has indicated that it can improve
learning sentiments. Learning sentiments will affect learning conditions. A system has been established
to detect and identify learners’ affections, and transmit information to conversational robots
so that learners can improve learning effectiveness (EG ¼ 82.7368, CG ¼ 70.3158) and motivation
and the teaching strategies can be adjusted. It is sufficient to prove that it is beneficial to students’
self-directed learning (d¼0.2562>0.2). |
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| 全文 | ![Full Text]() |
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| DOI | https://doi.org/10.1080/10447318.2024.2351708 |
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| 系統號 | NO000007064 |
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