Journal of Computing in Higher Education

Abstract

HyFlex learning environments have been meeting the unique needs of students and institutions for nearly 20 years. However, it was the pandemic that gave HyFlex its widespread acceptance and application. Literature suggests that HyFlex may now be considered part of the new norm in education and therefore, further study is needed on how it affects both teaching and learning. Our flipped design thinking course leverages active learning requiring the instructor and students to interact extensively. We piloted a specific version of HyFlex we named “Interactive Synchronous HyFlex” where students can participate on a daily basis in person or synchronously online. In this specific instance of HyFlex we explore: (1) Does student academic performance differ in the HyFlex environment compared to the Face to Face only environment? And (2) Does student academic performance differ based on how they chose to participate in the HyFlex course? Data were collected for this quasi-experimental study design on overall semester grades and three significant design projects during the semester. We compared the course offered as a Face to Face only experience to the course offered as a HyFlex course enabling remote participation. Second, we parse students in the HyFlex course into two categories: those who did not participate remotely vs. those who participated remotely once or more times. Students in the HyFlex course had a significantly different grade distribution earning more A’s and more F’s than their Face to Face only counterparts. Given the positive results of the Interactive Synchronous HyFlex approach, we plan to continue implementing it in our introductory design course though we will increase our attention on the remote students as they may need additional scaffolding to be successful.

Abstract

Cheating in online exams without face-to-face proctoring has been a general concern for academic instructors during the crisis caused by COVID-19. The main goal of this work is to evaluate the cost of these dishonest practices by comparing the academic performance of webcam-proctored students and their unproctored peers in an online gradable test. With this aim in mind, we carried out a randomized field experiment using a simple video surveillance system through Google Meet during an online closed-book final exam of an Introduction to Microeconomics course. Given that all conditions except for webcam monitoring were identical, differences in between-subjects scores are attributed to academic dishonesty. After controlling for potential confounding factors, including gender, academic degree, instructor, previous score and whether students were repeaters or not, we found that those students who were proctored via webcam obtained statistically significant lower scores in the final exam than those who were not using this surveillance system with a low level of invasiveness. Inspection of the potential factors behind these differences in scores suggests that the poorer performance of proctored students is more related to academic dishonesty than to reasons involving anxiety or heterogeneity factors.

Abstract

Institutions of higher education are interested in supporting the academic success of their students in the most effective ways possible. Increasingly, this means engaging students in a blend of both online and in-person learning activities as well as connecting students with supportive communities in both modalities. This research explores the efforts of an institution that is trying to create positive post-secondary learning experiences for thousands of adults who have experienced significant barriers to accessing higher education through traditional routes. Students around the world are supported through both online and local, in-person communities created to support their academic engagement. In this study we used social network analysis to examine and compare the influence of both in-person and online support communities on student affective and cognitive engagement. We also compared the strength of engagement support from peers, teachers, and personal family/friend networks. We found significant differences in the strength, frequency, and type of support offered by the online and in-person aspects of the program as well as in the students’ self-reported engagement and enjoyment between the two modalities. While in-person communities in this context had the greatest impact on both blended and in-person student engagement, the online community also had a significant effect on student engagement. This research adds to the blended learning literature by illustrating that course communities are not only distinguished based on time and actors, but also by modality. Support communities that occur in blended and online contexts affect student engagement in different, and often complementary, ways.

Abstract

Sentiment Analysis (SA), a technique based on applying artificial intelligence to analyze textual data in natural language, can help to characterize interactions between students and teachers and improve learning through timely, personalized feedback, but its use in education is still scarce. This systematic literature review explores how SA has been applied for learning assessment in online and hybrid learning contexts in higher education. Findings from this review show that there is a growing field of research on SA, although most of the papers are written from a technical perspective and published in journals related to digital technologies. Even though there are solutions involving different SA techniques that can help predicting learning performance, enhancing feedback and giving teachers visual tools, its educational applications and usability are still limited. The analysis evidence that the inclusion of variables that can affect participants’ different sentiment expression, such as gender or cultural context, remains understudied and should need to be considered in future developments.

Abstract

The aim of this study is to examine the development of self-regulated learning (SRL) of university students in an EFL course via Flipped classroom through a novel measurement roadmap. Microanalytic techniques were used throughout the process rather than students’ perceptions at a given moment. SRL skills scores are reported as well as sample testimonies from students as qualitative data used to explain the analytic measures. The study was conducted with 12 students studying at a public university and lasted for 6 weeks. A new system FCMWEB is designed throughout to monitor online SRL development taking Zimmerman (2008) SRL model as a basis. While the forethought phase was monitored in the online sessions and the performance and self-reflection phase were associated with the face-to-face sessions. Records from FCMWEB as microanalytic, worksheet, observation notes and self-reflection form were used as data collection tools. During the study, the sub skills of forethought phase, self-reflection phase and performance phase are analyzed and validated through students’ perspectives. The developments in the skills of the forethought and self-reflection phases were between sufficient and advanced levels. The performance phase was mostly sufficient, but also included poor and advanced levels. The results provide implications for course designers and instructors who desire to provide a better flipped classroom experience in EFL for university students.

Abstract

This paper offers a synthesis on computing identity and the experiences of women and minoritized populations in computing and computer science in higher education. Examining computing identity and its role in the computing experiences of minoritized undergraduates can help us better understand ways to engage and support women and minoritized individuals in the computing field thus increasing participation and persistence of these groups in computing. In this article, we present a review of research literature on computing identity within the experiences of women and minoritized undergraduate students in computing. The research questions guiding this work are: (1) What research literature exists about computing identity?, (2) According to existing literature, what are the experiences of women and racially minoritized undergraduates in computing (e.g., persons who identify as Black, Hispanic/Latinx, Indigenous people)?, and (3) What theoretical frameworks are used to guide existing computing identity literature? Emergent themes include the need to focus on exposure to computing, persistence, career expectations, and engagement. While there is no consensus on a computer identity framework, there is research guided by social cognitive career theory, social identity theory, and practice theory. We conclude that computing identity, including its multiple conceptualizations, offers multiple opportunities for informing and broadening participation of minoritized populations in computing. Future research should include further conceptual exploration of computing identity.

Abstract

The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining can predict learning outcomes. This work aims to provide support for learners and instructors regarding efficient learning with computer-based learning environments (CBLEs). We evaluated log file and questionnaire data from students (N = 58) who used a CBLE for two weeks. Results show a significant learning increase after studying with the CBLE with a very high effect size (p < .001, g = 1.71). A cluster analysis revealed two groups with significantly different learning outcomes accompanied by different navigation patterns. The time spent on learning-relevant pages and the interactivity with a CBLE are meaningful indicators for Recall and Transfer performance. Our results show that navigation behaviors indicate both beneficial and detrimental learning processes. Moreover, we could demonstrate that navigation behaviors impact the learning outcome. We present an easy-to-use approach for learners as well as instructors to promote successful learning by tracking the duration spent in a CBLE and the interactivity.

While the significance of motivation in the adoption of mobile learning has been well-documented in numerous studies, empirical evidence regarding the roles of cognitive, social, and affective needs remains limited. This presents a notable gap in the field of education concerning the influence of motivational factors on mobile learning acceptance. To address this gap, our study adopts a motivational perspective by extending the Technology Acceptance Model (TAM) with the Uses and Gratifications Theory (UGT). Our primary objective is to investigate the motivational variables influencing university students’ behavioral intention to use mobile learning. We collected data from 7,426 university students through an online survey. Subsequently, we employed factor analysis and the structural equation modeling for analysis. Our proposed model demonstrated a remarkable explanatory power, accounting for 76.7% of behavioral intention. Notably, the findings highlight the paramount influence of constructs rooted in the uses and gratifications theory (specifically, social needs, cognitive needs, and affective needs) on behavioral intention. These needs emerge as fundamental motivators in shaping the intention to use mobile learning. This study contributes valuable empirical evidence by incorporating the uses and gratifications theory into the technology acceptance model, shedding light on how this integration influences the intention to use mobile learning. It underscores the substantial roles played by cognitive, affective, and social needs in the realm of mobile learning. In light of these findings, the study delves into both theoretical and practical implications, offering a foundation for future research endeavors.

Although learning analytics dashboards (LADs) are being recognized as tools that can enhance engagement—a crucial factor for the success of asynchronous online higher education—their impact may be limited without a solid theoretical basis for motivation. Furthermore, the processes through which students make decisions using dashboards and engage are not well understood. This study aimed to design a LAD informed by self-determination theory and to investigate university students’ experiences with it. The findings, including those from stimulated recall interviews using eye-tracking data, shed light on how the LAD fosters student engagement. Interacting with the LAD fulfilled students’ basic psychological needs. Awareness and reflection on learning status facilitated by the LAD boosted enthusiasm for active learning participation. The LAD offered essential information to support autonomous, strategic decisions, empowering students to take proactive actions toward personal goals while reinforcing their belief in achieving them. Despite its potential benefits, various improvements have been identified to further enhance its effectiveness. Based on the findings, we discuss the implications of this study for future research in the field.

Computer science can be included in Early Childhood Education (ECE) through the use of block-based coding and robots. But this requires adequate preparation of ECE teachers to work with coding and robots, and integrate such into high quality lesson plans. In this paper, we investigate predictors of lesson plan quality among preservice, early childhood teachers learning to teach with robots. Motivation variables, academic standing, and collaboration status during lesson planning were entered as predictors of overall lesson plan quality, front-end analysis quality, STEM and robotics integration quality, and instructional activities quality. Achievement emotions in STEM was a positive predictor and mathematics interest was a negative predictor of the overall lesson plan quality score. Achievement emotions in STEM was a significant positive predictor of front-end analysis score. Science and technology interest and individual lesson planning were significant positive predictors of teaching and learning activities design score. Instructional implications are presented.

In recent years, embodied learning has gained currency in the field of education, allowing interactivity between users, thus contributing to collaborative learning in the flow of embodied immersive technology. Evidence based studies conducted in this field tackled the effectiveness of this approach on students’ performance and learning outcomes in children’s education. However, scarcity of scoping reviews treating the outcome of using embodied collaborative learning on higher education students’ performance was detected. Considering the relevance of building a theoretical background guiding further research in this current field, this meta-analysis was conducted to fill the gap. This article describes the current issues on research about embodied collaborative learning in STEM education in XR learning settings to identify advances and gaps. Published papers between 2013 and 2023 were selected from educational databases, identifying 12 documents related to the subject of interest of this meta-analysis. Results show that embodied learning have positive impact on social interactivity and collaboration between students. Positive impact on students’ academic outcomes was also detected. Alongside with the preceding, embodied collaborative learning has a positive impact on overall students’ social flow (motivation, cohesion, emotions, interaffectivity, satisfaction). This article presents a theoretical background for embodied collaborative testing tools based on embodied social presence and collaboration practical criteria.