Journal of Computing in Higher Education

Cheung, S.K.S.; Wang, Fu Lee; Kwok, Lam For

doi: 10.1007/s12528-023-09350-9pmid: 36714821

Simonova, Ivana; Faltynkova, Ludmila; Kostolanyova, Katerina; Klimszova, Slavomira

doi: 10.1007/s12528-022-09332-3pmid: 35990928

During the covid-19 pandemic, schools at all levels were often closed and online distance instruction (ODI) was applied. The main objective of this research was to discover the main didactic features of online distance instruction; and based on the collected data to define didactic recommendations towards improving the quality of the process. Five hypotheses were set that evaluated students’ opinions in the areas of teachers’ support for learners within ODI, types of sources exploited within ODI, means used for practising and fixing new knowledge within ODI, assessment of learners’ performance within ODI, and students’ feedback on ODI. In total, 272 respondents from upper secondary and higher education institutions participated in the research. Each respondent described the process of online distance instruction in two courses they selected of 64: (1) in a course that they appreciated, liked, enjoyed, and considered efficient from the point of view of their learning; (2) in a course that caused them discomfort in learning, as it was conducted in a way that did not suit them, and their learning did not bring the expected learning outcomes. Data were collected via a questionnaire; Chí-square test, adjusted residuals, and t test for comparison of means were calculated. Before the research started, teachers were trained in online distance instruction. Therefore, we expected that they will be competent in designing online distance courses and the courses will follow didactic principles. The results discovered significant differences in the frequency of occurrence of observed features in courses that received positive feedback compared to those having negative evaluation. However, some exceptions were detected.

Hew, Khe Foon; Huang, Weijiao; Du, Jiahui; Jia, Chengyuan

doi: 10.1007/s12528-022-09338-xpmid: 36101883

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.

Xie, Youru; Huang, Yuling; Luo, Wenjing; Bai, Yucheng; Qiu, Yi; Ouyang, Ziru

doi: 10.1007/s12528-022-09348-9pmid: 36618325

The interaction between teachers and students is vital for promoting teaching quality. Online learning spaces have various features that can support teacher-student interaction in online learning contexts. In this study, a preliminary model was developed by analyzing the principles underlying the interaction between teachers and students and the support features of online learning spaces. Then, the interaction model was refined and validated in three rounds of teaching practice involving 31 college students. A real-time dynamic artificial intelligence analysis system was used to analyze the teacher-student interaction during three rounds of design-based research. The results showed that the model significantly fostered students’ engagement during the interaction. Moreover, students significantly improved their final exam scores and their innovative problem-solving ability after the intervention.

Gomez, David R.; Swann, William; Willms Wohlwend, Mary; Spong, Stephanie

doi: 10.1007/s12528-022-09330-5pmid: 35813579

This case study examines the adaptation of an existing online, asynchronous faculty development resource at the University of New Mexico to support the unanticipated need for all instructors to teach remotely starting in spring 2020, due to the COVID-19 pandemic. The course—entitled Evidence-Based Practices for Teaching Online (EBPTO)—was previously utilized to support instructor transitions to distance education by applying constructivist principles to the development of evidence-based online teaching practices. The course was adapted to address institutional and instructor needs as a result of the pandemic, including increasing facilitation resources. The largest EBPTO cohort, with 117 participants, began in June 2020. Data were collected through a reflective journal administered at the mid-point and an end-of-course survey. Analysis of the reflective journal provided insight into participants’ learning experience in terms of key “takeaways,” LMS tools that they had the opportunity to practice, and “lingering questions” that they had. The top 3 takeaways were the usefulness of course mapping, the usefulness of backwards design, and the deepening familiarity with LMS tools. Results from the end-of-course survey showed positive feedback from participants regarding perceived achievement of the course learning objectives, even after scaling the course to accommodate the large number of instructors moving to remote instruction.

Han, Feifei; Ellis, Robert A.

doi: 10.1007/s12528-022-09333-2pmid: 35971519

This study investigated the relations between students’ self-reported perceptions of the blended learning environment, their observed online learning strategies, and their academic learning outcomes. The participants were 310 undergraduates enrolled in an introductory course on computer systems in an Australian metropolitan university. A Likert-scale questionnaire was used to examine students’ perceptions. The digital traces recorded in a bespoke learning management system were used to detect students’ observed online learning strategies. Using the data mining algorithms, including the Hidden Markov Model and an agglomerative hierarchical sequence clustering, four types of online learning strategies were found. The four strategies not only differed in the number of online learning sessions but also showed differences in the proportional distribution with regard to different online learning behaviors. A one-way ANOVA revealed that students adopting different online learning strategies differed significantly on their final course marks. Students who employed intensive theory application strategy achieved the highest whereas those used weak reading and weak theory application scored the lowest. The results of a cross-tabulation showed that the four types of observed online learning strategies were significantly associated with the better and poorer perceptions of the blended learning environment. Specially, amongst students who adopted the intensive theory application strategy, the proportion of students who self-reported better perceptions was significantly higher than those reporting poorer perceptions. In contrast, amongst students using the weak reading and weak theory application strategy, the proportion of students having poorer perceptions was significantly higher than those holding better perceptions.

Yang, He; Cai, Jin; Yang, Harrison Hao; Wang, Xiaochen

doi: 10.1007/s12528-022-09322-5pmid: 35637707

With the outbreak of the COVID-19 pandemic, blended learning became exceptionally widespread, especially in higher education. As a result, many college students became beginners in this learning method. To identify key factors that impact beginners’ continuance intention in blended learning, this study surveyed 1845 first-year college students at a university in central China in the falls of 2020 and 2021 who used blended learning for the first time. Structural equation modeling was employed to verify a model that integrates intrinsic motivation and academic self-efficacy in the Expectation-Confirmation Model of Information System Continuance. The results show that performance expectancy, intrinsic motivation, and satisfaction significantly impact beginners’ continuance intention in blended learning. Moreover, performance expectancy, intrinsic motivation, and confirmation significantly impact beginners’ continuance intention through mediating variable satisfaction. Academic self-efficacy does not directly impact college students’ continuance intention but indirectly impacts their continuance intention through intrinsic motivation. Finally, this study provides suggestions for educators to improve beginners’ blended learning experience thus promoting their continuance intention in blended learning.

Jong, Morris Siu-Yung

doi: 10.1007/s12528-022-09334-1pmid: 36091926

Flipped classroom (FC) is a “blended” instructional approach that requires students to complete pre-lecture individual learning tasks in preparation for participating in related in-lecture peer learning activities. One of the critical problems of FC has been students’ lack of motivation to complete the assigned online pre-lecture tasks prior to attending the corresponding face-to-face lectures. Spherical video-based immersive virtual reality (SV-IVR), which can be produced without costly computing equipment and sophisticated technical expertise, is a technological tool with considerable potential for enhancing teaching and learning. This mixed-methods study was grounded in the instructional motivation theory of ARCS (Attention, Relevance, Confidence and Satisfaction). A total of 188 education students (i.e., pre-service teachers) who were generally knowledgeable about the pedagogical concept of FC evaluated the ARCS motivational affordances of SV-IVR in support of the pre-lecture stage of FC. These students were from teaching majors of (i) language education, (ii) social and humanities education, and (iii) mathematics and science education. The results indicated the participants across the 3 majors positively perceived SV-IVR as having desirable benefits on “A,” “R,” and “S,” but not “C.” This research provides new insights into adopting SV-IVR in FC, in particular, shedding light on leveraging this technological tool in pre-service teacher education.

Zou, Di; Xie, Haoran; Wang, Fu Lee

doi: 10.1007/s12528-022-09337-ypmid: N/A

Peer, teacher, and self-feedback have been widely applied in English writing courses in higher education. However, few studies have used technology to activate the potential of feedback in project-based collaborative learning or discussed how technology-enhanced peer, teacher and self-feedback may assist students’ writing, promote their critical thinking tendency, or enhance their engagement in learning, so we investigated them in this research. A total of 90 students, 30 in each group, participated in it. They reported their progress at four stages every other week, received peer, teacher, and self-feedback respectively for 10 weeks, and submitted their finalized review articles in week 14. Before the treatment, we evaluated the students’ writing proficiency and critical thinking tendency through a pre-test and a pre-questionnaire survey. After the treatment, we evaluated their collaborative writing products and conducted a post-questionnaire survey to measure their critical thinking tendency and behavioral, cognitive, and emotional engagement in learning. The results indicated that technology-enhanced peer and teacher feedback were significantly more effective than self-feedback in assisting collaborative writing; peer and self-feedback were significantly more effective than teacher feedback in promoting critical thinking tendency, enhancing behavioral and emotional engagement in learning; and teacher feedback was significantly more effective than self-feedback in enhancing cognitive engagement in learning. We also conducted semi-structured interviews to investigate their perception of the three feedback types and the technology-enhanced feedback-assisted collaborative writing experience. Most students enjoyed the writing experience and regarded the use of digital tools effective for its implementation. Based on these results, we suggest that teachers implement more technology-enhanced peer and self-feedback assisted collaborative writing.

Li, Kam Cheong; Wong, Billy Tak-ming

doi: 10.1007/s12528-022-09341-2pmid: N/A

This paper reports a comprehensive review of literature on personalised learning in STEM and STEAM (or STE(A)M) education, which involves the disciplinary integration of Science, Technology, Engineering, and Mathematics, as well as Arts. The review covered the contexts of STE(A)M education where personalised learning was adopted, the objectives of personalised learning and research issues, and various aspects of practising personalisation. A total of 72 publications from 2011 to 2020 were collected from Scopus for review. The results reveal the widespread studies in this area across various countries/territories, levels of education, subject disciplines, and modes of education. The most common objective of personalised learning lied in catering for learning styles. The issue most frequently addressed focused on evaluating the effectiveness of technologies for personalised learning. Blended learning and learning analytics are the most popular means to achieve personalised learning. Among various aspects of learning, learning material is the one most frequently addressed. Also, the factors and criteria for personalising learning were summarised, which reveal the heterogeneous nature of learners who have their own learning ability, interest, style and progress. The results suggest more research on interdisciplinary and integrative approaches for STE(A)M learning to examine how personalisation can be applied effectively, as well as more investigation on integrating personalisation with the pedagogies and elements commonly introduced to STE(A)M education.