The Impact of Students’ Perceptions of Online Learning Environments on Students’ Satisfaction in the Context of Covid-19 Pandemic

In the context of the Covid-19 pandemic, the present study aimed to examine students’ perceptions of online learning environments and students’ satisfaction based on their academic stream. The study also investigated the impact of students’ perceptions of online learning environments on students’ satisfaction. A quantitative descriptive survey method was applied. This study included 230 students (130 undergraduate and 100 postgraduate students) from colleges and universities of West Bengal. Online Learning Environments Survey, an adapted and translated (Bengali) version of the Distance Education Learning Environments Survey (DELES) by Scott L Walker (2003), was used for collecting data. For data analysis, statistical techniques, ANOVA and regression analysis were performed. The results revealed significant mean differences among arts, commerce, and science students’ perceptions of online learning environments in the dimensions of student interaction and collaboration, personal relevance, authentic learning, active learning, and student autonomy except in instructor support. Furthermore, a significant mean difference in student satisfaction was found based on the academic stream. The result revealed that overall students’ perceptions of online learning environments had a significant impact on student satisfaction, with student interaction and collaboration being the most significant predictor of all; however, instructor support, active learning, and student autonomy were not found to be significant predictors of student satisfaction.

Developing a Cornerstone "Human in the System" Engineering Design Course

The authors describe their experiences creating a cornerstone engineering design course for mechanical and industrial engineering undergraduate students. Starting with a tabula rasa, we have been working to create a one-semester design experience that integrates Human Factors (HF) directly into every aspect of engineering design. In the last decade, we have identified three key issues with which we grapple: lack of integration of HF in design; lack of access to cohesive HF data; and dysfunctional student teams. Given the lack of available information upon which to draw for the design of this course, we adopted a CQI-like iterative, organic, and evolutionary approach. In this paper, we present many of the ways we have attempted to address these issues, relating to courseware development, course management, assessment and grading, and student and instructor support. We summarize by presenting our advice to others who are looking to fully embed HF or other non-design fields into a cogent design experience for their students. All our courseware and tools are available freely on the web.

Developing a Cornerstone "Human in the System" Engineering Design Course

The authors describe their experiences creating a cornerstone engineering design course for mechanical and industrial engineering undergraduate students. Starting with a tabula rasa, we have been working to create a one-semester design experience that integrates Human Factors (HF) directly into every aspect of engineering design. In the last decade, we have identified three key issues with which we grapple: lack of integration of HF in design; lack of access to cohesive HF data; and dysfunctional student teams. Given the lack of available information upon which to draw for the design of this course, we adopted a CQI-like iterative, organic, and evolutionary approach. In this paper, we present many of the ways we have attempted to address these issues, relating to courseware development, course management, assessment and grading, and student and instructor support. We summarize by presenting our advice to others who are looking to fully embed HF or other non-design fields into a cogent design experience for their students. All our courseware and tools are available freely on the web.

Validation of a Four Factor Measure: Scale of Perceived Instructor Support

Academic-related stressors are common for college students, such as future career decisions or pressures to succeed academically. Furthermore, the impact of health and finance issues may add to the burden. Perceived support from an academic community, peers, or family can provide a buffer to mitigate the effects of these stressors. Several studies have emphasized the importance of support by instructors in particular and found that students’ perceptions of instructor support can counteract academic stress and promote retention. The purpose of the present study was to validate a scale for instructor support, which consisted of four factors: autonomy, expectation, interpersonal relationships, and engagement. A confirmatory factor analysis demonstrated good fit for the items within each factor. Results also indicated that students who planned to return to the university next semester were more likely to report higher levels of autonomy and expectation. The Scale of Perceived Instructor Support (SPIS) is a short, 24 item-inventory that can be used by faculty advisors as part of a formal advising practice or informally by class instructors.

Omani Undergraduate Students’ Awareness and Experiences of the Research-Teaching Nexus

The research-teaching nexus is an important factor in the enhancement of the quality of teaching and learning in higher education institutions. The purpose of the study was to explore undergraduate students’ awareness and experiences of research in one faculty at Sohar University, Oman. Data were gathered from 240 undergraduate students using an online survey. Overall, results indicated that while there was good evidence of students’ awareness and experiences of research, less than half of the students in the sample were aware of or had experienced important research activities. Some students reported advantages arising from their participation in research—including developing research skills and gaining new knowledge. They also reported the need for more hands-on research experience and instructor support. Some findings were generally consistent with the literature on students’ awareness and experiences of research. The study provided important implications for the research-teaching nexus at Sohar University.

Validation of a Four Factor Measure: Scale of Perceived Instructor Support (SPIS)

Academic-related stressors are common for college students, such as future career decisions or pressures to succeed academically. Furthermore, the impact of health and finance issues may add to the burden. Perceived support from an academic community, peers, or family can provide a buffer to mitigate the effects of these stressors. Several studies emphasized the importance of support by instructors in particular and found that students’ perceptions of instructor support can counteract academic stress and promote retention. The purpose of the present study was to validate a scale for instructor support, which consisted of four factors: autonomy, expectation, interpersonal relationships, and engagement. A confirmatory factor analysis demonstrated good fit for the items within each factor. Results also indicated that students who planned to return to the university next semester were more likely to report higher levels of autonomy and expectation. The Scale of Perceived Instructor Support (SPIS) is a short, 24 item-inventory that can be used by faculty advisors as part of a formal advising practice or informally by class instructors.

The impact of knowledge sharing enablers on knowledge sharing behavior: an empirical study

Purpose Academic institutions play a crucial role in social and economic development. They share responsibilities to equip students with knowledge and skills. This study aims to examine and investigate the impact of knowledge sharing enablers (KSE) on knowledge sharing behavior (KSB). The paper measured KSE through perceived instructor support of knowledge sharing instructor support (IS), perceived information and communication technology (ICT) support of knowledge sharing and perceived ability to share knowledge (ASK). Design/methodology/approach A survey questionnaire was used as an instrument for data collection. A sample of 597 students from Al Ain University in UAE participated in the study. The collected data were treated and analyzed through MS Excel and International Business Machines Statistical Package for the Social Sciences (SPSS) version 25. The theory of reasoned action (TRA) was used in formulating a conceptual framework. Several statistical techniques, including partial least square structural equation modeling, were used to test and verify hypotheses. Findings Findings of the study supported TRA theory by suggesting a positive and significant impact of KSE (IS, ICT and ASK) on KSB. The findings supported the stated three hypotheses and confirmed that at least 45% of the variation in students’ KSB is explained by a variation in one of the three KSE indicators. The paper provided important theoretical and practical implications for researchers and managers of academic institutions. Originality/value Academic institutions need to advance their strategies to create more collaborative environments for boosting knowledge sharing among students. Such practice will contribute in improving the students’ overall capabilities, skills and success of academic institutions.

Specifications Grading: What It Is, and Lessons Learned

Traditional point-based grading is failing students entering a competency-based workforce: Employers require concrete skills and knowledge, not “high” grades. In the specifications approach, learning outcomes are explicitly linked to the grading system. The basic components of the approach include clear alignment of learning outcomes to certification standards, bundled sequences of assessments tied to basic and advanced competency/learning outcomes, pass/fail grading with no partial credit, opportunities to revise unacceptable work, and detailed expectations of performance on assessments. This article describes the specifications approach and provides examples highlighting how to (1) align course learning objectives with a grading system, (2) implement a pass/fail approach even for complex assessment, (3) define specifications, (4) create and sequence bundles of assessments, and (5) provide instructor support through feedback and tokens.