Cited by 245Intelligent Tutoring Systems and Adaptive LearningOnline and Blended LearningSocial Robot Interaction and HRI

The DOI matches its Crossref record; 53 of the 54 references it cites were found in a registry or an index.

Using chatbots to support student goal setting and social presence in fully online activities: learner engagement and perceptions

Open access

Hew, Khe Foon, Huang, Weijiao, Du, Jiahui, Jia, Chengyuan·2023·Journal of Computing in Higher Education

DOI 10.1007/s12528-022-09338-xPMC PMC9458299

Open this paper in CoChat — free account Open PDF

Abstract

Although fully online learning is now the 'new normal' in many parts of the world, its implementation is often beset by challenges such as the lack of student self-regulation, and the sense of isolation. In this paper, we explored the use of chatbots to support student goal setting (Study 1) and social presence (Study 2) in online activities. In Study 1, participants in a fully online course were invited to complete a goal setting activity prior to attending class via a goal-setting chatbot. The chatbot engaged participants with five questions developed based on the SMART (specific, measurable, achievable, realistic, and timely) goal setting framework. In Study 2, English-as-Foreign-Language participants in a fully online course were tasked to complete listening practices. The learning buddy chatbot was designed based on the social presence framework (interpersonal communication, open communication, cohesive communication) to guide students through listening exercises. In both Study 1 and 2, we evaluated participants' behavioral engagement by measuring their conversation records with the chatbots, as well as participants' perceived usefulness and ease of use of the chatbots. We also gathered in-depth interview data concerning the participants' perceptions of interacting with the chatbots. Overall, our findings found positive learner experiences with both chatbots with regard to the chatbots' perceived usefulness and perceived ease of use. We also provided suggestions for instructors to apply chatbots in teaching and learning.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1007/s12528-022-09338-x

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · cited 3×
“Perceived usefulness is “the degree to which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989, p. 320).”
BackgroundMethodInfluential
Journal of Physics: Conference Series
Jui, J. J., Mohd Helmi, S., Mohd Riduwan, G., Mohd Ashraf, A., & Mohd Zaidi, M. T. (2013) · Journal of Physics Conference Series · doi:10.1088/issn.1742-6596 · Cited by 15,799
Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-013-0528-y · Cited by 12,038 · cited 1×
“Purposeful sampling is widely used in qualitative research to identify information-rich cases related to the phenomenon of interest (Palinkas et al., 2015).”
Background
Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education
Garrison, D. R., Anderson, T., & Archer, W. (1999) · The Internet and Higher Education · doi:10.1016/s1096-7516(00)00016-6 · Cited by 6,619 · cited 1×
“Social presence can be defined as “the ability of participants to project themselves socially and emotionally, as real people” (Garrison et al., 1999, p. 94).”
Background
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · cited 1×
“The first chatbot, ELIZA, developed in 1966, simulated a psychotherapist’s conversation with humans, where users could communicate with ELIZA by entering text inputs, and the chatbot would respond in kind (Weizenbaum, 1966).”
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022 · cited 2×
“According to social response theory (Nass & Moon, 2000), human–computer interactions are basically social where humans have the innate tendency to perceive computers as social beings, even when they know that machines do not have feelings or intentions.”
Background
Development and use of the ARCS model of instructional design
Keller, J. M. (1987) · Journal of Instructional Development · doi:10.1007/bf02905780 · Cited by 2,332 · cited 2×
“It is therefore suggested that in the long-term use of chatbot, it is important to add variety to sustain the interest in learning with the chatbot (Keller, 1987), by either simplifying or making some changes to the reoccurring sentences.”
Background
Self-regulation through goal setting
Latham, G. P., & Locke, E. A. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90021-k · Cited by 1,373
AI-based chatbots in customer service and their effects on user compliance
Adam, M., Wessel, M., & Benlian, A. (2021) · Electronic Markets · doi:10.1007/s12525-020-00414-7 · Cited by 1,195 · cited 3×
“By interacting with an anthropomorphized machine, a user may perceive a sense of social presence (Adam et al., 2021).”
BackgroundInfluential
From cognitive modeling to self-regulation: a social cognitive career path.
Zimmerman, B. J. (2013) · Educational Psychologist · doi:10.1080/00461520.2013.794676 · Cited by 991 · cited 1×
“These self-reflections can influence subsequent forethought processes (Zimmerman, 2013).”
Background

Show all 54 references

Research works printed but not linked: 1

Doran, G. T. (1981). There’s a SMART way to write management’s goals and objectives. Management Review, 70(11), 35–36.

Sorted by citations

Students’ voices on generative AI: perceptions, benefits, and challenges in higher education
Chan, C. K. Y., & Hu, W. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00411-8 · Cited by 2,301
Large language models in education: a focus on the complementary relationship between human teachers and ChatGPT
Jeon, J., & Lee, S. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11834-1 · Cited by 696
“…more complex structures designed by commercial developers for language learning (e.g., Wang et al., 2023), and (3) customized chatbots created by researchers or teachers for particular language learning contexts using visual chat-bot development platforms (e.g., Hew et al., 2023; Lee & Jeon, 2022).”
Background
Exploring the potential of an AI-based Chatbot (ChatGPT) in enhancing English as a Foreign Language (EFL) teaching: perceptions of EFL Faculty Members
Mohamed, A. M. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-11917-z · Cited by 387
“Moreover, a study by Hew et al. ( 2023) revealed that faculty members appreciated the convenience and accessibility of chatbots in providing instant feedback to students.”
Using AI-driven chatbots to foster Chinese EFL students’ academic engagement: An intervention study
Wang, Y., & Xue, L. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108353 · Cited by 328
Exploring the role of intrinsic motivation in ChatGPT adoption to support active learning: An extension of the technology acceptance model
Lai, C. Y., Cheung, K. Y., & Chan, C. S. (2023) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2023.100178 · Cited by 310
The impact of different conversational generative AI chatbots on EFL learners: An analysis of willingness to communicate, foreign language speaking anxiety, and self-perceived communicative competence
Wang, C., Zou, B., Du, Y., & Wang, Z. (2024) · System · doi:10.1016/j.system.2024.103533 · Cited by 308
Assessing student-perceived impact of using artificial intelligence tools: Construction of a synthetic index of application in higher education
Grájeda, A., Burgos, J., Olivera, P. C., & Sanjinés, A. (2023) · Cogent Education · doi:10.1080/2331186x.2023.2287917 · Cited by 266
“Chatbots, simulating human conversations, have proven effective in increasing student engagement and learning outcomes (Abbas et al., 2022; Baskara, 2023; Hew et al., 2022).”
Unleashing ChatGPT's Power: A Case Study on Optimizing Information Retrieval in Flipped Classrooms via Prompt Engineering
Wang, M., Wang, M., Xu, X., Yang, L., Cai, D., & Yin, M. (2023) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2023.3324714 · Cited by 199
“Many studies have shown that AI-based chatbots can play a variety of roles, such as learning chatbots [15], [16], [17], assistant chatbots [18], [19], and mentor chatbots [20], [21].”
Background
A systematic review of research on speech-recognition chatbots for language learning: Implications for future directions in the era of large language models
Jeon, J., Lee, S., & Choi, S. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2023.2204343 · Cited by 143
“…studies of text-based chatbots, in which, besides serving as conversational partners, they have performed such functions as analyzing students ’ needs (Jeon, 2021), fostering students ’ goal-setting and social presence (Hew et al., 2023), and providing online video guidance (Fidan et al., 2022).”
Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania
Rudolph, J., Mohamed Ismail, F. M., & Popenici, S. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/54fs5e77 · Cited by 189
“It can be especially challenging to get students to come together in groups to discuss and collaborate in some contexts (Hew et al., 2023).”
Background
Effects of GenAI-empowered interactive support on university EFL students' self-regulated strategy use and engagement in reading
Pan, M., Lai, C., & Guo, K. (2024) · The Internet and Higher Education · doi:10.1016/j.iheduc.2024.100991 · Cited by 145
Effects of a ChatGPT-based flipped learning guiding approach on learners’ courseware project performances and perceptions
Li, H. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8923 · Cited by 159
“In ChatGPT-FLGA, students might use the AI teacher to obtain the relative answers immediately, which exceeded the support of other intelligent chatbots for learning (Hew et al., 2023), el evating students’ performance on the courseware projects (Joo et al., 2000).”
Method
How educational chatbots support self-regulated learning? A systematic review of the literature
Guan, R., Raković, M., Chen, G., & Gašević, D. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12881-y · Cited by 182
“…and other task features (Bailey et al., 2021; Lin & Chang, 2020; Jones & Castellano, 2018; Chen et al., 2020), task-related tips (Tian et al., 2021), opportunities for progress check relative to task topics (Harati et al., 2021), and questions for goal setting (Du et al., 2021; Hew et al., 2023).”
Students' voices on generative ai: perceptions, benefits, and challenges in higher education
Chan, C. K. Y., & Hu, W. (2023) · arXiv · doi:10.48550/arxiv.2305.00290 · Cited by 2,504
Exploring English language learning via Chabot: A case study from a self determination theory perspective
Annamalai, N., Eltahir, M. E., Zyoud, S. H., Soundrarajan, D., Zakarneh, B. M., & Alsalhi, N. R. (2023) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2023.100148 · Cited by 127
Investigating the usefulness of artificial intelligence-driven robots in developing empathy for English for medical purposes communication: The role-play of Asian and African students
Derakhshan, A., Teo, T. P., & Khazaie, S. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108416 · Cited by 109
Evaluating AI's impact on self-regulated language learning: A systematic review
Chang, W.-L., & Sun, J. C. (2024) · System · doi:10.1016/j.system.2024.103484 · Cited by 134
Perceived satisfaction of university students with the use of chatbots as a tool for self-regulated learning
Sáiz-Manzanares, M. C., Marticorena-Sánchez, R., Martín-Antón, L. J., González Díez, I., & Almeida, L. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e12843 · Cited by 96
“Using technological resources—such as chatbots—that promote real-time interaction about the questions and issues students may have throughout their learning processes is important in effectively personalizing these processes [58].”
Background
Chatbots in education: A systematic review of objectives, underlying technology and theory, evaluation criteria, and impacts
Debets, T., Banihashem, S. K., Brinke, D. J.-T., Vos, T. E. J., Wenniger, G. M. D. B., & Camp, G. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105323 · Cited by 124
What can online traces tell us about students’ self-regulated learning? A systematic review of online trace data analysis
Du, J., Hew, K. F., & Liu, L. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104828 · Cited by 79
Self-citation
Chatbots and AI in Education (AIEd) tools: The good, the bad, and the ugly
Ifelebuegu, A. O., Kulume, P., & Cherukut, P. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.29 · Cited by 109
Effect of an AI-based chatbot on students’ learning performance in alternate reality game-based museum learning
Liang, H., Hwang, G., Hsu, T., & Yeh, J. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13448 · Cited by 78
Preparing preservice teachers to teach with digital technologies: An update of effective SQD-strategies
Tondeur, J., Trevisan, O., Howard, S. K., & van Braak, J. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105262 · Cited by 109
A Structural equation modeling analysis of generative AI chatbots adoption among students and educators in higher education
Saihi, A., Ben-Daya, M., Hariga, M., & As'ad, R. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100274 · Cited by 75
The use of chatbots in university EFL settings: Research trends and pedagogical implications
Klímová, B., & Ibna Seraj, P. M. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1131506 · Cited by 69
The Future of Work: Understanding the Effectiveness of Collaboration Between Human and Digital Employees in Service
Le, K. B. Q., Sajtos, L., Kunz, W. H., & Fernandez, K. V. (2024) · Journal of Service Research · doi:10.1177/10946705241229419 · Cited by 77
“Furthermore, DEs are also being investigated for their potential to share goals with teachers in managing students in education settings (Hew et al. 2022).”
A review of integrating AI-based chatbots into flipped learning: new possibilities and challenges
Lo, C. K., & Hew, K. F. (2023) · Frontiers in Education · doi:10.3389/feduc.2023.1175715 · Cited by 89
Self-citation
Chatbots and Flipped Learning: Enhancing Student Engagement and Learning Outcomes through Personalised Support and Collaboration
Baskara, F. R. (2023) · IJORER International Journal of Recent Educational Research · doi:10.46245/ijorer.v4i2.331 · Cited by 78
Students-Generative AI interaction patterns and its impact on academic writing
Kim, J., Lee, S.-S., Detrick, R., Wang, J., & Li, N. (2025) · Journal of Computing in Higher Education · doi:10.1007/s12528-025-09444-6 · Cited by 97
“This structural mastery can contribute to more polished and professional outcomes (Hew et al., 2023 ).”
AI-driven Technology and Chatbots as Tools for Enhancing English Language Learning in the Context of Second Language Acquisition: A Review Study
AbuSahyon, A. S. E., Alzyoud, A., AlShorman, O., & Al-Absi, B. (2023) · International Journal of Membrane Science and Technology · doi:10.15379/ijmst.v10i1.2829 · Cited by 102
“In addition, chatbots are available 24/7, enabling learners to practice at their own exercises and tasks [65].”
Background
Reviewing the performance of AI detection tools in differentiating between AI-generated and human-written texts: A literature and integrative hybrid review
Chaka, C. (2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.1.14 · Cited by 85
Investigating the effect of artificial intelligence in education (AIEd) on learning achievement: A meta-analysis and research synthesis
Tlili, A., Saqer, K., Salha, S. H., & Huang, R. (2025) · Information Development · doi:10.1177/02666669241304407 · Cited by 92
Do AI chatbots impact motivation? Insights from a preliminary longitudinal study
Liu, M., & Reinders, H. (2024) · System · doi:10.1016/j.system.2024.103544 · Cited by 68
Artificial Intelligence‐Supported Student Engagement Research: Text Mining and Systematic Analysis
Chen, X., Xie, H., Qin, S. J., Wang, F. L., & Hou, Y. (2025) · European Journal of Education · doi:10.1111/ejed.70008 · Cited by 52
Revisiting Integrated Model of Technology Acceptance Among the Generative AI ‐Powered Foreign Language Speaking Practice: Through the Lens of Positive Psychology and Intrinsic Motivation
Wang, C., Li, X., & Zou, B. (2025) · European Journal of Education · doi:10.1111/ejed.70054 · Cited by 58
Shall I use ChatGPT? A study on perceived trust and perceived risk towards ChatGPT usage by teachers at higher education institutions
Bhaskar, P., Misra, P., & Chopra, G. (2024) · International Journal of Information and Learning Technology · doi:10.1108/ijilt-11-2023-0220 · Cited by 60
A systematic literature review on designing self-regulated learning using generative artificial intelligence and its future research directions
Xia, Q., Liu, Q., Tlili, A., & Chiu, T. K. F. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105465 · Cited by 77
Integrating AI chatbots into the metaverse: Pre-service English teachers’ design works and perceptions
Hwang, Y., Lee, S., & Jeon, J. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12924-4 · Cited by 53
“…provide diverse language learning affordances, such as social interaction (Huang et al., 2022), goal-oriented language learning (Hew et al., 2023), task-based language learning (Jeon, 2022), communication opportunities (Ji et al., 2023), and language-related feedback provision (Hew et al., 2023).”
Influential
Artificial intelligence literacy in assessment: Empowering pre‐service teachers to design effective exam questions for language learning
Coşgun, G. E. (2025) · British Educational Research Journal · doi:10.1002/berj.4177 · Cited by 67
Knowledge-Based and Generative-AI-Driven Pedagogical Conversational Agents: A Comparative Study of Grice’s Cooperative Principles and Trust
Wölfel, M., Shirzad, M. B., Reich, A., & Anderer, K. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc8010002 · Cited by 51
“Most existing implementations are designed for specific tasks, such as question generation [37,38], increasing social engagement [32,33], language learning [39] or math tasks [40,41], as well as feedback systems like AutoTutor [30,35].”
Background
Examining the Effectiveness of AI-integrated Approach in EFL Writing: A Case of ChatGPT
Harunasari, S. Y. (2023) · International Journal of Progressive Sciences and Technologies · doi:10.52155/ijpsat.v39.2.5516 · Cited by 72
Method of the development of students' foreign language communication skills based on practice with a chatbot
Sysoyev, P. V., & Filatov, E. M. (2023) · Perspectives of science and education · doi:10.32744/pse.2023.3.13 · Cited by 43
Potentials of ChatGPT in Computer Programming: Insights from Programming Instructors
Husain, A. (2024) · Journal of Information Technology Education Research · doi:10.28945/5240 · Cited by 61
“Moreover, a study by Hew et al. (2023) reveal ed that faculty members appreciate the convenience and accessibility of AI chatbots in providing immediate responses, which help save time and reduce workload for students and teachers.”
Background
Solving the Self-regulated Learning Problem: Exploring the Performance of ChatGPT in Mathematics
Li, P., Lee, H.-Y., Cheng, Y., Starčič, A. I., & Huang, Y. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-40113-8_8 · Cited by 45
Exploring the impact of robot interaction on learning engagement: a comparative study of two multi-modal robots
Fung, K. Y., Fung, K. C., Lui, T. L. R., Sin, K. F., Lee, L., Qu, H., & Song, S. (2025) · Smart Learning Environments · doi:10.1186/s40561-024-00362-1 · Cited by 44
It Is Not the Huge Enemy: Preservice Teachers’ Evolving Perspectives on AI
Uwosomah, E. E., & Dooly, M. (2025) · Education Sciences · doi:10.3390/educsci15020152 · Cited by 33
Generative AI-driven personalization of the community of inquiry model: enhancing individualized learning experiences in digital classrooms
Anderson, J. E., Nguyen, C. A., & Moreira, G. (2025) · The International Journal of Information and Learning Technology · doi:10.1108/ijilt-10-2024-0240 · Cited by 33
Designing a Chatbot for Contemporary Education: A Systematic Literature Review
Ramandanis, D., & Xinogalos, S. (2023) · Information · doi:10.3390/info14090503 · Cited by 44
From prompt to polished: Exploring student-chatbot interactions for academic writing assistance
Usher, M., & Amzalag, M. (2025) · Education Sciences · doi:10.3390/educsci15030329 · Cited by 31
Gaze-Driven Adaptive Learning System With ChatGPT-Generated Summaries
Santhosh, J., Dengel, A. R., & Ishimaru, S. (2024) · IEEE Access · doi:10.1109/access.2024.3503059 · Cited by 36
Virtual Tutor, Digital Natives and AI: Analyzing the impact of ChatGPT on academia in Indonesia
Margono, H., Saud, M., & Falahat, M. (2024) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2024.101069 · Cited by 26
Exploring the dynamics of ChatGPT: Students and lecturers perspectives at an open distance e-learning university
Sevnarayan, K. (2024) · Journal of Pedagogical Research · doi:10.33902/jpr.202426525 · Cited by 34
Investigating the Support Provided by Chatbots to Educational Institutions and Their Students: A Systematic Literature Review
Ramandanis, D., & Xinogalos, S. (2023) · Multimodal Technologies and Interaction · doi:10.3390/mti7110103 · Cited by 60
“The students that utilized the ECAs that were developed by Hew et al. [55] also declared that they would like a chatbot that utilizes human-like conversational characteristics, can handle small talk and provide personalized, accurate and fast responses.”
BackgroundMethod
Integrating AI Chatbots in ESL and CFL Instruction: Revolutionizing Language Learning with Artificial Intelligence
Yingsoon, G. Y., Chua, N. A., Rahman, N., Suyan, Z., & Yiming, C. (2024) · LatIA · doi:10.62486/latia202423 · Cited by 37
Can rule-based educational chatbots be an acceptable alternative for students in higher education?
Güldal, H., & Dinçer, E. O. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12977-5 · Cited by 27
“Similarly, Hew et al. (2022) also emphasize the possibility of 24/7 access to the chatbot.”
Mobile-based artificial intelligence chatbot for self-regulated learning in a hybrid flipped classroom
Han, I., Ji, H., Jin, S., & Choi, K. (2026) · Journal of Computing in Higher Education · doi:10.1007/s12528-025-09434-8 · Cited by 24
“Other researchers have also examined how chatbot-based SRL prompting can facilitate college-level online learners’ SRL by assisting them with planning and goal setting (Du et al., 2021; Hew et al., 2023; Song & Kim, 2021).”
Gamification bolsters self-regulated learning, learning performance and reduces strategy decline in flipped classrooms: A longitudinal quasi-experiment
Maimaiti, G., & Hew, K. F. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105278 · Cited by 33
Self-citation
Impact of pre-knowledge and engagement in robot-supported collaborative learning through using the ICAPB model
Zhao, J., Yang, Q., Lian, L.-W., & Wu, X. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105069 · Cited by 25
Generative AI technology and language learning: global language learners’ responses to ChatGPT videos in social media
Chen, Z., Wei, W., & Zou, D. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2511248 · Cited by 38
“This shift in responsibility may potentially decrease students ’ overall satisfaction with utilise AI technologies (Hew et al., 2022), and (3), students ’ limited feedback literacy may reduce learner satisfaction, which negatively impacts students ’ intrinsic motivation and ability to continuously…”
Designing chatbots in language classrooms: an empirical investigation from user learning experience
Wiboolyasarin, W., Wiboolyasarin, K., Tiranant, P., Boonyakitanont, P., & Jinowat, N. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00319-4 · Cited by 35
“Furthermore, as highlighted in review studies by Hew et al. (2023) and Hwang and Chang (2023), chatbot research in education has primarily employed quantitative approaches in design.”
Background
Chatbots in higher education: a systematic review
Lambebo, E. A., & Chen, H. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2436931 · Cited by 29
“Chatbots assist students in setting learning objectives, engaging with course materials, personalizing learning, providing 24/7 assistance, encouraging group involvement, encouraging critical thinking, and ultimately lowering dropout rates in HE (Hew et al., 2023; Ilieva et al., 2023).”
A study on the influencing factors of university students’ online persistent learning supported by intelligent technology in the post-pandemic era: an empirical study with PLS-SEM
Shi, G., Li, J., & Yang, J. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2023.2205901 · Cited by 22
“Researchers highlighted the importance of social presence in online learning (Hew et al., 2023; Norz et al., 2023), because social presence enhanced the intimate relationship and nonverbal interaction between peers, established a harmonious relationship, and allowed learners to obtain better…”
Facilitating Online Self-Regulated Learning and Social Presence Using Chatbots: Evidence-Based Design Principles
Huang, W., & Hew, K. F. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3523199 · Cited by 32
Self-citation
Online Learning
Singh, A., Singh, D., & Chhikara, S. (2024) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-0409-9.ch004 · Cited by 23
The Double-Edged Sword: AI Integration in English Language Education from the Perspectives of Iranian EFL Instructors
Parviz, M. (2024) · Estudios Ingleses de la Universidad Complutense · doi:10.5209/cjes.97261 · Cited by 29
A systematic and bibliometric review of artificial intelligence in sustainable education: Current trends and future research directions
Abulibdeh, A. O. (2025) · Sustainable Futures · doi:10.1016/j.sftr.2025.101033 · Cited by 39
Designing artificial intelligence chatbots for self-regulated learning from a systematic review based on Habermas's three interests
Wu, X.-Y., Radloff, J., Yeter, I. H., Wang, L., & Chiu, T. K. F. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2563086 · Cited by 32
“Teachers examine and verify AI-generated suggestions for SRL (Hew et al., 2023; Ng et al., 2024).”
The future of language education: Teachers’ perceptions about the surge of AI writing tools
Zimotti, G., Frances, C., & Whitaker, L. (2024) · Technology in Language Teaching & Learning · doi:10.29140/tltl.v6n1.1136 · Cited by 19
AI Chatbots for Language Practices
Nguyen, N. H. V., & Ho, P. V. P. (2024) · International journal of AI in language education. · doi:10.54855/ijaile.24115 · Cited by 18
The study on the influence factors of intention to continue using MOOCs: integrating UTAUT model and social presence
Li, Y., & Zhao, M. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2318562 · Cited by 19
“Researchers have highlighted the importance of social presence in online learning (Hew et al., 2023; Norz et al., 2023).”
Optimizing Student Support. A Review of the Use of AI Chatbots in Higher Education
Segovia-García, N. (2024) · European Public & Social Innovation Review · doi:10.31637/epsir-2024-324 · Cited by 34
Investigating the capabilities of large language model-based task-oriented dialogue chatbots from a learner’s perspective
Lee, J. H., Shin, D., & Hwang, Y. (2024) · System · doi:10.1016/j.system.2024.103538 · Cited by 21
FUNDAMENTAL AND BASIC COGNITIVE SKILLS REQUIRED FOR TEACHERS TO EFFECTIVELY USE CHATBOTS IN EDUCATION
Kerneža, M. (2023) · International Baltic Symposium on Science and Technology Education (BalticSTE) · doi:10.33225/balticste/2023.99 · Cited by 17
“The number of studies exploring the use of chatbots in education is increasing (e.g., Kuhail et al., 2023; Yildiz Durak, 2023; Hew et al., 2023).”
Background
Old tales, new tools: How AI chatbots and the metaverse are transforming premodern classical literature reading activities
Baek, J., & Hwang, Y. (2024) · International Journal of Educational Research · doi:10.1016/j.ijer.2024.102461 · Cited by 17
A Systematic Review of the Recent Research on the Usefulness of Chatbots for Language Education
Kızıl, A. Ş., Klímová, B., Pikhart, M., & Parmaxi, A. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70001 · Cited by 32
From Passive Watching to Active Learning: Empowering Proactive Participation in Digital Classrooms with AI Video Assistant
Bodonhelyi, A., Thaqi, E., Özdel, S., Bozkir, E., & Kasneci, E. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713513 · Cited by 26
“In online settings, engagement often encompasses not only traditional indicators like contributing to discussions and asking questions [14, 80], but also involves consistent participation in virtual activities such as live chats [34], quizzes [53], and collaborative tasks [39].”
Chatbots in tertiary education: Exploring the impact of warm and competent avatars on self‐directed learning
Richter, S., Kishore, S., Piven, I. P., Dodd, P., & Bate, G. W. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.13610 · Cited by 19
AI versus teachers and peers: a comparative study on speaking performance, willingness to communicate, self-perceived communicative competence and foreign language anxiety
Wang, C.-H., & Zou, B. (2025) · International Review of Applied Linguistics in Language Teaching · doi:10.1515/iral-2024-0310 · Cited by 24
Integrating AI chatbots in informal digital English learning: impacts on listening competencies in Chinese higher education
Zhou, Q., Hashim, H., & Sulaiman, N. A. (2025) · Education and Information Technologies : Official Journal of the IFIP technical committee on Education · doi:10.1007/s10639-025-13811-2 · Cited by 22
“Similarly, Hew et al. ( 2023) applied the SMART framework (specific, measurable, achievable, realistic, timely) to analyze chatbot-based learning and found that chatbots enhance listening development by fostering goal-setting behaviors and social presence in digital learning environments.”
Multi-level students’ sense of community development in hybrid and online learning environments at higher educational institutions: a systematic literature review
Lu, H., & Zhang, X. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2023.2214803 · Cited by 19
“There were also around 4% of the studies that expanded the territories outside the classrooms to online communities initiated by students or faculties in various social medial platforms (e.g. Charteris et al., 2018; Hew et al., 2022; Su & Chan, 2017).”
A Q method study on Turkish EFL learners’ perspectives on the use of AI tools for writing: Benefits, concerns, and ethics
Virlan, A. Y., & Tomak, B. (2024) · Language Teaching Research · doi:10.1177/13621688241308836 · Cited by 27
“On the other hand, some learners acknowledge the practicality of AI technologies and employ them to complete academic tasks and gain insights into the modules being studied (Hew et al., 2023).”
Unpacking the Rejection of L2 Students Toward ChatGPT-Generated Feedback: An Explanatory Research
Chen (陈子淇), Z., Wei (韦卫), W., Zhu (祝新华), X., & Yao (姚远), Y. (2026) · ECNU Review of Education · doi:10.1177/20965311241305140 · Cited by 16
“…technology (Celik, 2023; Hatlevik et al., 2018; Fryer et al., 2020), and (3) the disconnect between students ’ external requirements and their interactions with technology has resulted in minimal use of chatbots in their learning process (Ericsson et al., 2023; Guo et al., 2023; Hew et al., 2023).”
Promoting students’ motivation in language education with gamified pedagogical conversational agents
Khosrawi-Rad, B., Keller, P. F. G., Benner, D., Grogorick, L., Borchers, A., Janson, A., Leimeister, J. M., & Robra-Bissantz, S. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105374 · Cited by 24
AI Chatbots in Higher Education: Opportunities and Challenges for Personalized and Mobile Learning
Mourabit, I. E., Andaloussi, S. J., Ouchetto, O., & Miyara, M. (2025) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v19i12.54163 · Cited by 21
Promoting engagement in online learning beyond COVID‐19: Possible strategies and directions for future research
Hew, K. F., & Huang, W. (2023) · Future in Educational Research · doi:10.1002/fer3.9 · Cited by 15
Self-citation
Educational Psychology Aspects of Learning with Chatbots without Artificial Intelligence: Suggestions for Designers
Černý, M. (2023) · European Journal of Investigation in Health Psychology and Education · doi:10.3390/ejihpe13020022 · Cited by 22
“Sriwisathiyakun and Dhamani-tayakul [50] talk about the chatbot being an educational tool that has a natural feel and, at the same time, is associated with minimal barriers, allowing it to be used for competency-based learning.”
Background
ParichartBOT: a chatbot for automatic answering for postgraduate students of an open university
Sakulwichitsintu, S. (2023) · International Journal of Information Technology · doi:10.1007/s41870-023-01176-z · Cited by 13
“This is also corresponding to research on the development of artificial intelligence systems for answering questions and having conversations with students automatically, and in the use of chatbots for providing educational information to students [3, 24].”
Background
Student satisfaction with artificial intelligence chatbots in Ethiopian academia
Subaveerapandiyan, A., Radhakrishnan, S., Tiwary, N., & Guangul, S. M. (2024) · IFLA Journal · doi:10.1177/03400352241252974 · Cited by 18
“Furthermore, their 24/7 availability and role in improving time management and academic performance have garnered attention (Hew et al., 2023).”
Integrating chatbot technology into English language learning to enhance student engagement and interactive communication skills
Zhang, J. (2025) · Journal of Computational Methods in Sciences and Engineering · doi:10.1177/14727978241312992 · Cited by 22
“The use of chatbots was discussed in paper, 12 which could help students ’ goal setting as well as their social presence during online activities.”
AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Tracking
Rashik, M., Sweth, S., Agrawal, N. A., Kochar, S., Smith, K. M., Rajabiyazdi, F., Setlur, V., Mahyar, N., & Sarvghad, A. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714280 · Cited by 18
“Outcomes of Study I suggest that utilizing traditional machine-learning models, such as decision trees and support vector machines [17, 26], is likely to yield unsatisfactory intent identification outcomes.”
Investigating AI Chatbots’ Role in Online Learning and Digital Agency Development
Engeness, I., Nohr, M., & Fossland, T. (2025) · Education Sciences · doi:10.3390/educsci15060674 · Cited by 22
“The integration of chatbots into online learning represents a promising advancement in digital education, offering benefits such as personalised learning, immediate feedback, and enhanced engagement (Hew et al., 2023; Jeon et al., 2023).”
Influential
Boosting Student Engagement in STEM : Integrating Large Language Model‐Based Virtual Agents Into Alternate Reality Games
Wang, M., Zhu, J., Hwang, G., Chang, S., Yang, Q., & Zhang, D. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70139 · Cited by 16
Effects of self-regulated vocabulary learning with chatbots on incidental and collocational vocabulary learning and foreign language learning boredom
Jalambo, M. O., Çakmak, F., & Akhter, S. (2025) · Discover Education · doi:10.1007/s44217-025-00977-7 · Cited by 17
“With interaction, learners can autonomously identify learning assets, plan strategies, and observe their learning journey [33].”
Autonomous Motivation, Self-Efficacy, and Developmental Regulation Processes in Distance Education Across Diverse Age Groups
Yaban, E. H., & Gaschler, R. (2025) · American Journal of Distance Education · doi:10.1080/08923647.2025.2484047 · Cited by 13
“Additionally, incorporating interactive tools, such as chatbots or gamification elements, into online programs can boost students’ confidence in regulating their learning (e.g., Bittner & Wellmann, 2022; Hew et al., 2023).”
The effects of text-based conversational teachable agents’ communicative features on student math learning: Tone style and emoji use
Lyu, B., Li, C., Li, H., & Xing, W. (2025) · Journal of Research on Technology in Education · doi:10.1080/15391523.2025.2511313 · Cited by 13
“…communicative features (e.g., tone styles, emoji use), influence its effectiveness in student learning, although prior research has indicated the impact of such communicative features on users’ perception and trust in conversational AI (Beattie et al., 2020; Hew et al., 2023; Yu & Zhao, 2024).”
Influential
Safeguarding Student Data
Emon, M. M. H., & Chowdhury, M. S. A. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-3316-8.ch008 · Cited by 11
Chatbots in Pharmacy: A Boon or a Bane for Patient Care and Pharmacy Practice?
Ramadhani, C. (2023) · Sciences of Pharmacy · doi:10.58920/sciphar02030001 · Cited by 14
“As such, they are best suited for use cases where user interactions are relatively simple and predictable (31).”
Background
Undergraduate students’ learning outcomes with ChatGPT: A meta-analytic study
Mo, F., Huang, J., Yang, Y., Ozen, Z., Maeda, Y., & Olenchak, F. R. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100536 · Cited by 22
Factors influencing engagement in EFL learning of higher education learners in blended learning environments
Cai, Q. (2025) · International Journal of Educational Research · doi:10.1016/j.ijer.2025.102587 · Cited by 10
EFL teachers’ formative assessment literacy and developmental trajectories: A comparative study of face-to-face and blended teaching modes
Meng, Y., Cui, Y. H., & Aryadoust, V. (2025) · System · doi:10.1016/j.system.2025.103694 · Cited by 10

Authors: Hew, K. F., Huang, W., Du, J., & Jia, C.
Affiliations: University of Hong Kong (HK)
Zhejiang University (CN)
Corresponding author: Hew, Khe Foon
ORCID: Hew, Khe Foon
Huang, Weijiao
Du, Jiahui
Jia, Chengyuan
Venue: Journal of Computing in Higher Education
Publisher: Springer Science and Business Media LLC
Published: 2022-09-09
Volume: 35
Issue: 1
Pages: 40-68
ISSN: 1042-1726 (ISSN-L)
1867-1233
DOI: 10.1007/s12528-022-09338-x
PMC: PMC9458299
OpenAlex: W4295753326
Cited by: 245
References: 54
Citations by year: 2026: 53 · 2025: 89 · 2024: 59 · 2023: 43 · 2022: 1
FWCI: 15.80
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Journal of Computing in Higher Education (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: University of Hong Kong (Teaching Development Grant)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Social Sciences › Education › Online and Blended Learning
Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
Keywords: chatbots, student goal setting, social presence, fully online learning, student engagement, student self-regulation, learner isolation, SMART goals, English as a foreign language, listening practices, perceived usefulness, perceived ease of use, learner perceptions

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Using chatbots to support student goal setting and social presence in fully online activities: learner engagement and perceptions

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks