Collaboration and interaction with smart mechanisms in flipped classrooms
| Date | 30 January 2023 |
| Pages | 625-642 |
| DOI | https://doi.org/10.1108/DTA-04-2022-0171 |
| Published date | 30 January 2023 |
| Author | Wu-Yuin Hwang,Rio Nurtantyana,Uun Hariyanti |
Collaboration and interaction with
smart mechanisms in
flipped classrooms
Wu-Yuin Hwangand Rio Nurtantyana
Graduate Institute of Network Learning Technology, National Central University,
Taoyuan, Taiwan, and
Uun Hariyanti
Graduate Institute of Network Learning Technology, National Central University,
Taoyuan, Taiwan and
Department of Information System, Faculty of Computer Science, Universitas
Brawijaya, Indonesia
Abstract
Purpose –This study aimed to investigate learning behaviors deeply in flipped classrooms. In addition, it is
worth considering how to help learners through recognition technology with natural language processing
(NLP) when learners have question and answer (Q&A). In addition, the Internet of Things (IoT) can be
utilized to make the physical learning environment more comfortable and smarter.
Design/methodology/approach –The authors developed smart learning environment (SLE) with smart
mechanisms supported by recognition technology, NLP and IoT to help learners and employed scaffolding to
facilitate their group discussions. This study is an explanatory research to investigate graduate learners’
learning behavior when they are collaborating with group members and interacting with the environment in
flipped classroom using the proposed SLE.
Findings –The results revealed that learners who collaborated more while coediting had significant
learning achievement, and NLP sufficiently addressed their questions. Physical conditions of the SLE were
comfortable for learners. They perceived that SLE could facilitate group discussions with scaffolding.
Practical implications –This study suggests to utilize flipped classrooms with technologies, e.g. Google
Slides integration, to help learners to do more collaboration and use smart mechanisms, e.g. Q&A with NLP,
to make learners more interacting during the discussion process.
Originality/value –The proposed SLE can record and analyze smartly their collaboration meaningfully
with group members and interact with the environment. Accordingly, researchers found that collaboration in
flipped classrooms can help their learning achievement, and it is worth being widely promoted.
Keywords Flipped classrooms, NLP, IoT, Smart learning environment, Coedit
Paper type Research paper
1. Introduction
Flipped classroom is an approach that allows learners to learn with interactive tasks, and it
has flexibility in terms of time or places to access the learning materials (Mojtahedi et al.,
The authors would like to express their deepest gratitude to Tzu-Hsin Huang (Carrie) for assisting and
helping in communicating with participants.
Funding: This study is partly funded through 109-2511-H-008-009-MY3 and 111-2410-H-008-061-
MY3, National Science and Technology Council, Taiwan.
Ethics approval: The research has acquired ethical approval. The research is original and has not
been published elsewhere. The manuscript has not been submitted to more than one journal for
simultaneous consideration.
Consent to participate: Informed consent was obtained from all individual participants included in
the study. Verbal informed consent was obtained prior to the interview.
Competing interest: The authors declared no potential conflicts of interest.
ThecurrentissueandfulltextarchiveofthisjournalisavailableonEmeraldInsightat:
https://www.emerald.com/insight/2514-9288.htm
625
Received 25 April 2022
Revised 22 December 2022
Accepted 22 December 2022
Data Technologies and
Applications
Vol. 57 No. 5, 2023
pp. 625-642
© Emerald Publishing Limited
2514-9288
DOI 10.1108/DTA-04-2022-0171
Smart
mechanisms in
flipped
classrooms
2020;Wu et al., 2017). Flipped classrooms are usually divided into three activities –pre-
class, during class and after class –for individual or group tasks (Zou et al., 2020;Cheng
et al., 2020). However, most of the 34 published papers reviewed by Zou et al. (2020) only
addressed the effectiveness of activities in flipped classrooms and compared it with other
methods without extensively investigating learning behaviors deeply. One possible reason
is that it is not easy to monitor learning behaviors in flipped classrooms, particularly for
collaboration behaviors such as recognizing individual contributions in group work,
including document preparation and presentation (Wang, 2009;Wu et al., 2017).
Several studieshave investigated the time learnersspent watching videos in the pre-class
activities, but no learners’activities were monitored after class (Zou et al., 2020;Cheng et al.,
2020;Mojtahedi et al., 2020;Jensen et al.,2018). In addition, these studies have suggested
facilitating learning with group discussions, such as learning with interactive learning
material before class and collaborative activities to construct knowledge during class.
Moreover, these activities can be efficiently accomplished by group discussions and group
feedback (Chu andKennedy, 2010;Greeno and Engeström,2014;Yang, 2016). T herefore, it is
worth investigating how group discussions and feedback help their learning deeply.
Collaborative activities in flipped classrooms were addressed as group discussions to
complete the specific task (Zou et al., 2020;Zheng et al., 2020;Wu et al., 2017). The use of
group tasks, such as collaborating to make reports or presentation slides, would construct
their understanding (Moffat et al., 2021;Lin and Hwang, 2018;Murillo-Zamorano and
Montanero, 2017). Through this collaboration, learners not only understand well their
perspectives but also exchange ideas with others and help complete the task quickly. On
the other hand, using technology such as real-time coedit with other learners while
collaborating can make learners have more engagement (Lin et al., 2016). Furthermore,
learners not only actively participate within groups such as group discussion or coedit but
also need to present their idea with slides and orally in class, after which they receive
feedback from other groups (Moffat et al., 2021;Hwang et al., 2006). However, a critical
problem in group discussion is that it is hard to monitor and analyze individual
contribution during group discussion and individual engagement during group
presentations. Previous studies suggested using traditional methods like voice recording
to monitor individual presentation contribution (Wang, 2009). However, to monitor learning
behaviors, recorded voices can be transcribed into texts with speech-to-text recognition
(STR) technology that could generate transcripts by recognizing speech content and display
it simultaneously on the screen or real-time transcription (Hwang et al., 2018). The
transcription can make participants learn information deeply because they use their
visual attention and understanding to analyze and to interpret the texts (Shadiev and
Sun, 2019). The transcript is also helpful in facilitating group discussions for learners to
refer back to the speech content after the presentation is finished.
Further, several studies mentioned that providing scaffoldings during group discussions
was helpful for learners to guide group discussions and to write their reports, e.g. the
scaffolding in reciprocal teaching, such as summarizing (S), questioning (Q), clarifying (C)
and prediction (P), abbreviated as “SQCP”(Tseng and Yeh, 2018;Okkinga et al., 2016). The
SQCP has advantages to establish a collaborative environment, organize the report content
and help learners’reflection (Tseng and Yeh, 2018).
During group discussions and oral presentations, learners sometimes have questions
related to the learning materials. On the other hand, advantages of artificial intelligent
methods such as automatically answering the question and semantic searching with
natural language processing (NLP) can help learners to answer the questions quickly
based on the material content (Brown et al., 2020;Chen et al., 2019a). In addition, the use
of Internet of Things (IoT) to control the physical environment can support the learning
environment situation based on their needs (Sretenovic et al., 2020;Kassab et al., 2019;
DTA
57,5
626
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