Journal of Applied Research in Higher Education 

About: Journal of Applied Research in Higher Education is an academic journal published by Babeș-Bolyai University. The journal publishes majorly in the area(s): Higher education & Computer science. It has an ISSN identifier of 1758-1184. Over the lifetime, 743 publications have been published receiving 4711 citations. The journal is also known as: Glamorgan journal of applied research in higher education & JARHE.

Technology adoption in higher education: a framework for identifying and prioritising issues and barriers to adoption of instructional technology

Abstract: This paper examines the issues and barriers that inhibit faculty from using technology in instruction. It uses the diffusion and adoption theory as a means to understand and explain how individuals and organisations react when an innovation is introduced into their environment. The framework proposed combines the empirical data from research using concept mapping with the theoretical factors identified from the literature to create a structured process that identifies the priority issues and barriers to technology adoption. Multidimensional scaling and cluster analysis were used to analyse the data gathered from the brainstorming session. A barrier definition and classification scheme was created and used to connect issues to barriers of adoption. Descriptive mixed methods approach was also used to develop a pictorial multivariate conceptual framework for understanding the relationships between issues and barriers to adopting instructional technology. Findings suggest that as a higher education institution in the early adoption phase of using instructional technology approaches critical mass of faculty users, it must address the issues of the critical mass, in order for the mainstream faculty to see the utility in the use of instructional technology in the classroom. This research lays the foundation for further research into the development of a systematic process or approach for managing the diffusion and adoption of technology in instruction at an institute of higher education.

The role of E-service quality in shaping online meeting platforms: a case study from higher education sector

Abstract: In this study, we have collected the response from 200 private university lecturers in Kurdistan Region of Iraq. In order to test the hypotheses, we have proposed structural equations modeling (SEM).,The purpose of this paper is to elaborate the direct and indirect effects of e-service quality on perceived value, satisfaction and willingness to pay for online meeting platforms in the education sector. This study also explores the effect of e-service quality on users' perception and satisfaction.,The results reveal that e-service quality directly affects the perceived value and satisfaction but has no direct effect on the willingness to pay. Secondly, perceived value and satisfaction mediated the relationships between service quality and willingness to pay. However, it is observed that perceived value has a more significant impact on the willingness to pay compared to satisfaction. It is further reported that perceived value is one of the antecedents of satisfaction. The study also explores the direct relationship between perceived value and willingness to pay, and introduces satisfaction as a mediating variable between perceived value and willingness to pay.,The sample is geographically limited as only online faculty and staff working at private universities participated in the study. This study has implications for administrators of higher educational institutions and companies providing IT solutions for online meetings. From a managerial standpoint, this study provides and IT companies a broad theoretical basis that designing a successful online meeting platform should specifically emphasize e-service quality, perceived value and customer satisfaction.,There is no study that evaluated the links among e-service quality, value, satisfaction, and willingness to pay for the online meeting platform services. Therefore, this study is useful for the private university administration and online meeting platform developers and investors.

What makes a good university lecturer? Students’ perceptions of teaching excellence

Abstract: Purpose – The purpose of this paper is to argue that, in order to achieve teaching excellence, student engagement in dialogue on this important matter is needed. Students’ conceptualisations of good teaching are fundamental when building an understanding of what this is and how it can be developed.Design/methodology/approach – This paper reports on findings of a qualitative study of undergraduate students’ perceptions of a good university lecturer. The paper draws on the secondary dataset collected by four subject centres of the Higher Education Academy (HEA).Findings – The interpretive analysis of the data shows that, from students’ perspectives, a combination of the lecturer's subject knowledge, willingness to help and inspirational teaching methods makes a good university lecturer. Being humorous and able to provide speedy feedback were also perceived as important factors. These findings have some important implications for academic practice.Originality/value – The key thesis advanced is that definitio...

Predicting student academic performance using multi-model heterogeneous ensemble approach

Abstract: The purpose of this paper is to empirically investigate and compare the use of multiple data sources, different classifiers and ensembles of classifiers technique in predicting student academic performance. The study will compare the performance and efficiency of ensemble techniques that make use of different combination of data sources with that of base classifiers with single data source.,Using a quantitative research methodology, data samples of 141 learners enrolled in the University of the West of Scotland were extracted from the institution’s databases and also collected through survey questionnaire. The research focused on three data sources: student record system, learning management system and survey, and also used three state-of-art data mining classifiers, namely, decision tree, artificial neural network and support vector machine for the modeling. In addition, the ensembles of these base classifiers were used in the student performance prediction and the performances of the seven different models developed were compared using six different evaluation metrics.,The results show that the approach of using multiple data sources along with heterogeneous ensemble techniques is very efficient and accurate in prediction of student performance as well as help in proper identification of student at risk of attrition.,The approach proposed in this study will help the educational administrators and policy makers working within educational sector in the development of new policies and curriculum on higher education that are relevant to student retention. In addition, the general implications of this research to practice is its ability to accurately help in early identification of students at risk of dropping out of HE from the combination of data sources so that necessary support and intervention can be provided.,The research empirically investigated and compared the performance accuracy and efficiency of single classifiers and ensemble of classifiers that make use of single and multiple data sources. The study has developed a novel hybrid model that can be used for predicting student performance that is high in accuracy and efficient in performance. Generally, this research study advances the understanding of the application of ensemble techniques to predicting student performance using learner data and has successfully addressed these fundamental questions: What combination of variables will accurately predict student academic performance? What is the potential of the use of stacking ensemble techniques in accurately predicting student academic performance?

An investigation in the effects of gender, prior academic achievement, place of residence, age and attendance on first‐year undergraduate attainment

Abstract: The number of people engaging in higher education (HE) has increased considerably over the past decade. However, there is a need to achieve a balance between increasing access and bearing down on rates of non‐completion. It has been argued that poor attainment and failure within the first year are significant contributors to the overall statistics for non‐progression and that, although research has concentrated on factors causative of student withdrawal, less attention has focused on students who fail academically. This study investigated the effects of a number of factors on the academic attainment of first‐year undergraduates within the Faculty of Humanities and Social Sciences at the University of Glamorgan. Results showed that gender and age had only minor impacts upon educational achievement, while place of residence, prior educational attainment and attendance emerged as significant predictors of attainment. Further analysis showed these three factors to be interrelated, with attendance correlating strongly with both entry points and place of residence. In turn, prior attainment was strongly linked to place of residence. Findings may be used to identify and proactively target students at risk of poor academic performance and dropout in order to improve rates of performance and progression.