The effect of the “Prediction-observation-quiz-explanation” inquiry-based e-learning model on flow experience in green energy learning

Hong, Jon‐Chao; Tsai, Chi Ruei; Hsiao, Hsien Sheng; Chen, Po Hsi; Chu, Kuan Cheng; Gu, Jianjun; Sitthiworachart, Jirarat

doi:10.1016/j.compedu.2019.01.009

Cited by 49 publications

(37 citation statements)

References 76 publications

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“…However, according to our study, flow experience had no effect on perceived usefulness, satisfaction, or intention to continue to use VRLs. There is still no consensus on flow as a determinant of satisfaction and intention to continue to use (Buil et al, 2018;Cheng, 2014a;Hong et al, 2019;Shin, 2006) or that flow is an indirect mediator influencing satisfaction and intention to continue using (Guo et al, 2016;Kang & Kim, 2018;Rodríguez-Ardura & Meseguer-Artola, 2016). Despite this lack of consensus, we suggest that instructors or institutions could enhance the extent of students' confirmation of their expectations of VRLs by providing them with optimal flow experiences.…”

Section: Discussionmentioning

confidence: 75%

Factors affecting Chinese university students’ intention to continue using virtual and remote labs

Zhang

et al. 2020

AJET

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Recently, virtual and remote labs (VRLs) have been developed to support students in conducting experiments in engineering and science education. However, little is known about the students’ intentions to continue using VRLs and their satisfaction with the experience. This study proposed an extended model embedded within the expectation confirmation model and two variables concerning flow experience (time distortion and focused attention) to predict Chinese university students’ satisfaction with and intention to continue using VRLs. A structural equation modelling technique based on covariance was conducted to evaluate survey questionnaire responses received from 238 students at a university located in central China. The results demonstrated that satisfaction was the most crucial determinant of the students’ intention to continue using VRLs, followed closely by perceived usefulness. Confirmation played an indirect role in predicting students’ intentions to continue using VRLs via satisfaction and perceived usefulness. Students’ flow experience while performing virtual experiments played a positive and direct role in confirming their expectations of VRLs.

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Section: Discussionmentioning

confidence: 75%

Factors affecting Chinese university students’ intention to continue using virtual and remote labs

Zhang

et al. 2020

AJET

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“…Siswa akan mengalami kesulitan dalam melaksanakan proses pembelajaran apabila tidak dilengkapi dengan media atau petunjuk pelaksanaan pembelajaran (Eliza et al, 2019). Untuk itu perlu dikembangkan LKS menggunakan model pembelajaran berbasis praktikum inkuiri yang didalamnya memuat sejumlah pertanyaan untuk menggiring siswa melaksanakan kegiatan praktikum dan menemukan konsep pembelajaran yang dipelajari (Hong et al, 2019).…”

Section: Pendahuluanunclassified

“…Metode inkuiri dan pemecahan masalah tidaklah berbeda (Hong et al, 2019). Pembelajaran menggunakan metode inkuiri dapat mengembangkan keterampilan dalam memecahkan masalah.…”

Section: Pendahuluanunclassified

“…Metode pembelajaran yang digunakan pada model pembelajaran berbasis praktikum inkuiri yaitu inkuiri, eksperimen, dan pemecahan masalah. Berbagai studi menyimpulkan bahwa metode inkuri lebih efektif secara signifikan dalam meningkatkan keterampilan berfikir (Hong et al, 2019;Theobald & Ramsbotham, 2019;Thuneberg et al, 2018).…”

Section: Pendahuluanunclassified

“…Model pembelajaran yang dapat digunakan untuk meningkatkan kemampuan siswa dalam menguasai konsep MRL dan melakukan praktikum MRL salah satunya adalah model pembelajaran berbasis praktikum inkuiri. Model pembelajaran berbasis praktikum inkuiri hanya dapat dilaksanakan pada mata pelajaran yang membutuhkan pemahaman konsep yang mendalam melalui kegiatan praktikum (Hong et al, 2019). Mata pelajaran MRL dengan materi Rangkaian Kemagnetan erat kaitannya dengan model pembelajaran berbasis praktikum inkuiri.…”

Section: Pendahuluanunclassified

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Pengembangan Perangkat Pembelajaran Berbasis Praktikum Inkuiri Untuk Mata Pelajaran Menganalisis Rangkaian Listrik

Candra

Usmeldi

Yanto

et al. 2020

JINoP

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The purpose of this study was to develop a valid, practical, and effective practicum-based learning tool on MRL subjects with the Magnetic Circuit material in SMKN 1 Padang consisting of RPP and LKS. This type of research is development research using a 4-D development model consisting of 4 stages, namely defining, designing, developing, and analyzing. The respondents of this study were students of class X TDTL-B SMKN 1 Padang consisting of 29 students. The results of data analysis obtained from the developed learning tools are categorized valid with the level of validity of the RPP and LKS are 85.42% and 87.50%. Learning Tools developed are categorized as practical with the practicality of teachers and students being 80% and 86.03%. The learning tools developed are effective in increasing students' competencies with classical completeness for cognitive, affective, and psychomotor competencies are 89.66%, 100%, and 100%. It can be concluded as a practicum-based learning tool developed which is a valid, practical, and effective learning tool.

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Research on Practice of P-PMCP Double Closed-Loop Hybrid Teaching Model—Taking Course of “Big Data Visualization” as an Example

Gao

Hong

Liang

et al. 2023

Computer Science and Education

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The effect of the “Prediction-observation-quiz-explanation” inquiry-based e-learning model on flow experience in green energy learning

Cited by 49 publications

References 76 publications

Factors affecting Chinese university students’ intention to continue using virtual and remote labs

Factors affecting Chinese university students’ intention to continue using virtual and remote labs

Pengembangan Perangkat Pembelajaran Berbasis Praktikum Inkuiri Untuk Mata Pelajaran Menganalisis Rangkaian Listrik

Research on Practice of P-PMCP Double Closed-Loop Hybrid Teaching Model—Taking Course of “Big Data Visualization” as an Example

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