Using achievement goal-based personalized motivational feedback to enhance online learning

Wang, Huanhuan; Lehman, James Daniel

doi:10.1007/s11423-021-09940-3

Cited by 28 publications

(12 citation statements)

References 49 publications

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“…As stated by Yeh et al (2019) there is a close connection with, learning strategies and behaviors of the students and their achievement goal orientations. Wang and Lehman (2021) claim that the achievement goal orientations of the students affected cognition, emotion, strategies adaptation, and motivation of the students might lead to differentiated support needs and learning outcomes. For this study, the focus of the students on the development of their skills and competence might affect their decision on their own goals and study methods as well as help them to determine the time they allocate to study the learning material.…”

Section: Discussion Conclusion and Suggestionmentioning

confidence: 99%

Examination of the correlation between e-learning readiness and achievement goal orientation of college students

SEVİM

Erol

Gülsoy

2023

Journal of Educational Technology and Online Learning

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Students’ readiness for e-learning is necessary in order to make the e-learning process more effective. Readiness for e-learning refers to the degree of having pre-knowledge and skills, and affective characteristics such as the necessary attitude and motivation to experience this process most effectively. Academic orientations of the students also contribute to their perception of the quality of the learning process in online learning environments. Furthermore, e-learning creates a learner-centered learning approach that might be contrived to personal goal orientations. Hence this study aims to identify the relationship between achievement goal orientations and the e-learning readiness level of the students. Data were collected from 457 university students enrolled in a public university in Turkey. The University Students’ E-learning readiness Scale and 2X2 achievement goal orientation scale were used as the data collection tools. A canonical correlation analysis (CCA) was performed to analyze the data. This study revealed that there is a statistically significant relationship between e-learning readiness and achievement goal orientations of the students. Three of the four canonical correlations were statistically significant which indicates that variables' linear combinations were related.

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Section: Discussion Conclusion and Suggestionmentioning

confidence: 99%

Examination of the correlation between e-learning readiness and achievement goal orientation of college students

SEVİM

Erol

Gülsoy

2023

Journal of Educational Technology and Online Learning

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“…In recent years, several studies have focused on data-driven learning analytics for this feedback type in OL (Lim et al, 2020(Lim et al, , 2021. Wang and Lehman (2021) found that personalized feedback supported regulating students' learning goals and behaviors and enhanced their learning performance.…”

Section: Feedback Mechanisms In Online Learningmentioning

confidence: 99%

Supporting the Instructional Videos With Chatbot and Peer Feedback Mechanisms in Online Learning: The Effects on Learning Performance and Intrinsic Motivation

Fidan

Gencel

2022

Journal of Educational Computing Research

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This study investigated the effects of artificial intelligence (AI)-based chatbot and peer feedback mechanisms integrated into the instructional videos (IVs) as a feedback tool on learning performance and intrinsic motivation of pre-service teachers (PTs) in online learning. The participants were 144 PTs from a university in Turkey. A pretest–posttest quasi-experimental design was adopted in this study. Two experimental (EG-1: Immediately elaborated feedback with a chatbot for IVs; EG-2: Delayed peer feedback with comments for IVs) groups and a control group (teaching with IVs) were selected. To collect qualitative data, a survey consisting of open-ended questions was conducted in the experimental groups. The results showed that the learning performance and intrinsic motivation scores of chatbot-based and peer feedback groups were higher than the scores in the traditional learning group. The implications for AI-powered feedback mechanisms and directions for future studies were discussed in this study.

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“…They are also encouraged to create a more supportive atmosphere which can lead to many discussions between the instructor and student. By doing so, instructors can help students to set and regulate their own goals, self-regulate strategies accordingly, and move forward to learn more, which positively affects students’ motivation (Wang and Lehman 2021). Based on their understanding from observations and discussions, instructors can provide more freedom with goals, strategies, learning sequences, paces, and repertoire that are more relevant to students lives, in addition to provide individualized feedback which students can properly connect to their own goals.…”

Section: Strategies For String Instructors and Discussionmentioning

confidence: 99%

Supporting Music Majors’ Learning: Motivational Strategies in College Music Lessons

Kim

2023

American String Teacher

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Using achievement goal-based personalized motivational feedback to enhance online learning

Cited by 28 publications

References 49 publications

Examination of the correlation between e-learning readiness and achievement goal orientation of college students

Examination of the correlation between e-learning readiness and achievement goal orientation of college students

Supporting the Instructional Videos With Chatbot and Peer Feedback Mechanisms in Online Learning: The Effects on Learning Performance and Intrinsic Motivation

Supporting Music Majors’ Learning: Motivational Strategies in College Music Lessons

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