Quality evaluation of online courses during COVID-19 pandemic based on integrated FCE-AHP method

Tang, Bin; Guo, Shiwei; Yeboah, Mathias; Wang, Zhenhua; Song, Cheng

doi:10.3233/jifs-210362

Cited by 8 publications

(16 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various methodologies and quantitative research methods have been employed in related studies, such as conducting an online survey of architecture students and analyzing data using descriptive statistics (Koh and Wong, 2021;Varma and Jafri, 2021;Peimani and Kamalipour, 2022;G€ uler, 2022), exploratory factor analyses (Asadpour, 2021), structural equation modeling (Tandon et al, 2021) and analytic hierarchy process (Tang et al, 2021). Other studies adopted qualitative analyses or mixed approaches, including semi-structured interviews and online surveys (Megahed and Hassan, 2022), experimental studies (Wu et al, 2021), surveys, case studies and structural equation modeling (Akçay Kavako glu et al, 2022) and focus group interviews, questionnaire surveys and statistical analyses (Ibrahim et al, 2021).…”

Section: Research Background and Gaps In Literaturementioning

confidence: 99%

“…The COVID-19 pandemic has had negative consequences for students on a large scale. The most prominent challenges include technical issues (Megahed and Hassan, 2022;Peimani and Kamalipour, 2021a;Ibrahim et al, 2021); technological complexity (Andiyan et al, 2021); lack of fast and stable Internet connection (Alnusairat et al, 2021;Peimani and Kamalipour, 2021a, b;Ibrahim et al, 2021;Asadpour, 2021;Andiyan et al, 2021;Milovanovi c et al, 2020;Alkhalil et al, 2021;Varma and Jafri, 2021;Elrawy and Abouelmagd, 2021;Gambo and Musonda, 2022;Bakir and Alsaadani, 2022;G€ uler, 2022;Khan and Thilagam, 2022;The Second Studio Podcast, 2020); difficulties in understanding teachers' instructions online (Alnusairat et al, 2021;Asadpour, 2021;Tandon et al, 2021;Elrawy and Abouelmagd, 2021;; increased sense of isolation and disconnection from peers and colleagues (Megahed and Hassan, 2022;Tang et al, 2021;Koh and Wong, 2021;Salama and Crosbie, 2020;Bakir and Alsaadani, 2022;Grover and Wright, 2020); psychological problems/negative feelings that could lead to alienation, uncertainty, confusion and identity loss (Megahed and Hassan, 2022;Ceylan et al, 2021;Alnusairat et al, 2021;Ibrahim et al, 2021;Gambo and Musonda, 2022;Tang et al, 2021;Archinect, 2020c); lack of privacy and proper work environment (home, dormitory etc.) (Cey...…”

Section: Content Analysismentioning

confidence: 99%

“…(Ceylan et al, 2021;Ibrahim et al, 2021;Peimani and Kamalipour, 2021b;Bakir and Alsaadani, 2022); lack of emotional connection (Alnusairat et al, 2021); lack of guidance and support (Alnusairat et al, 2021;Asadpour, 2021); insufficiency of self-discipline and concentration issues (Peimani and Kamalipour, 2021a;Varma and Jafri, 2021;Tandon et al, 2021;Ibrahim et al, 2021;Wu et al, 2021); low interaction and communication issues among students and between and students and instructors (Alnusairat et al, 2021;Tandon et al, 2021;Varma and Jafri, 2021;Elrawy and Abouelmagd, 2021;Tang et al, 2021;Peimani and Kamalipour, 2021b Ibrahim et al, 2021;; time and workload management (i.e. an increase in the number of tasks) (Alnusairat et al, 2021;Tandon et al, 2021;Varma and Jafri, 2021;Ibrahim et al, 2021;Andiyan et al, 2021;Bakir and Alsaadani, 2022;; increased boredom (due to too many tasks) (Andiyan et al, 2021); issues with the availability of up-to-date and appropriate hardware and software platforms (Ibrahim et al, 2021;Asadpour, 2021;Alnusairat et al, 2021;Milovanovi c et al, 2020;Varma and Jafri, 2021;Elrawy and Abouelmagd, 2021;Tang et al, 2021;Peimani and Kamalipour, 2021b;Andiyan et al, 2021;Gambo and Musonda, 2022;Salama and Crosbie, 2020;…”

Section: Content Analysismentioning

confidence: 99%

Section: Research Background and Gaps In Literaturementioning

confidence: 99%

See 3 more Smart Citations

Effects of the COVID-19 pandemic on architectural education: bibliometric and content analyses

Metinal

Ayalp²

2022

OHI

View full text Add to dashboard Cite

PurposeThe impact of the coronavirus disease 2019 (COVID-19) pandemic on architectural education (AE) was investigated, and a framework was proposed to reduce the impacts' negative consequences.Design/methodology/approachSystematic literature review, bibliometric and content analyses were combined to gain an in-depth understanding of the effects of the pandemic on AE and projections for its future. Relevant documents were extracted from the Web of Science (WoS) database. Bibliometric connections in the context of AE and COVID-19 pandemic were explored using text-mining and content analysis was performed.FindingsThe challenges, development tendencies and collaboration networks in AE during the pandemic were quantitatively and qualitatively analyzed. The most influential articles, journals, authors and countries/regions were highlighted using a bibliometric analysis. The analysis of keyword tendencies and clusters indicates that new concepts have emerged in AE research during the pandemic involving online, in-person and hybrid education. Using content analysis of 57 subtopics, 39 (18) were categorized as having negative (positive) effects. A comprehensive mitigation framework was designed to reduce the impact of the pandemic on AE.Research limitations/implicationsThe study findings can enable practitioners to construct effective solutions to COVID-19- and other disaster-related problems regarding AE. The implications, obstacles and mitigation framework presented can help identify gaps in the literature and guide further research.Originality/valueThis paper presents the first bibliometric and content analysis of AE and COVID-19 pandemic-related studies published from January 2020 to June 2022 to highlight several research directions and academic development within the field.

show abstract

Section: Research Background and Gaps In Literaturementioning

confidence: 99%

Section: Content Analysismentioning

confidence: 99%

Section: Content Analysismentioning

confidence: 99%

Section: Research Background and Gaps In Literaturementioning

confidence: 99%

See 2 more Smart Citations

Effects of the COVID-19 pandemic on architectural education: bibliometric and content analyses

Metinal

Ayalp²

2022

OHI

View full text Add to dashboard Cite

show abstract

“…Brown and Krzic ( 15 ) compared three different methods of teaching and taught using videos, laboratory manuals, and assignments, and combining synchronous and asynchronous and virtual laboratories were fundamental and the critical first step in transitioning to online teaching and learning. Tang et al ( 16 ) used Fuzzy Comprehensive Evaluation-Analytic Hierarchy Process (FCE-AHP) to quantitatively evaluate the quality of online courses and divided the evaluation criteria into four major indicators and 14 s-level indicators. Hou et al ( 17 ) created a way to investigate students’ perception of online courses in terms of teaching presence, cognitive presence, and online modality.…”

Section: Introductionmentioning

confidence: 99%

Impact of Online Courses on University Student Visual Attention During the COVID-19 Pandemic

Gao

2022

Front. Psychiatry

View full text Add to dashboard Cite

BackgroundUnder the threat of COVID-19, many universities offer online courses to avoid student gatherings, which prevent teachers from collecting responses and optimizing courses. This work collected eye movement data to analyze attention allocation and proposed instruction for improving the courses.MethodsSubjects were recruited to watch three online courses. Meanwhile, their eye movement data were collected through Dikablis Glasses. Mayer’s multimedia cognitive theory was adopted to discriminate the pivotal components of online course, and the Mann–Whitney relevance analysis demonstrated that different representations of courses affected the viewers’ attention differently.ResultsThree subjects watched three different types of political courses. Course 1, which combined text and explanation, attracted the most attention. Course 2 was shown to be less attractive than course 1 and better than course 3, but the subjects were distracted by the animations in course 2. Course 3, which did not use any technique to present learning content, attracts the least attention from the subjects. A correlation analysis shows that course 1 and course 3 have similar results compared with course 2.ConclusionOnline courses have become a norm during the COVID-19 pandemic. Improving the quality of online courses can effectively reduce the impact of the epidemic on teaching. These experiment results suggest that text + commentary in the design of online courses can effectively attract the attention of the listeners and achieve better learning results. Attention gradually rises in the early stage and then falls after reaching a peak. At this time, the proper introduction of animation can effectively reverse the attention curve, while individual text or commentary results in quickly losing the listener’s attention.

show abstract

Course Quality Evaluation of Higher Integrated Distance Education Based on Group Decision-making Algorithm

Wang,

Wang

2024

Preprint

View full text Add to dashboard Cite

Higher integrated distance education courses involve an educational process where students with and without disabilities learn together. The course quality evaluation methods of these courses require indicators that fully consider the conditions of different students. Due to the significant differences among students, the methods primarily based on the superposition of personal evaluations cannot be applied to these two special student groups. It leads to a lack of consensus and balance in the course quality evaluation and lower quality and accuracy in decision-making. To solve this problem, this paper proposes a group decision-making algorithm for the quality evaluation of higher integrated distance education courses. In a large, differentiated student group, the decision-making results are formed by collecting, integrating, and weighing group members' opinions, knowledge, experience, and other information. Firstly, the algorithm proposed uses the K-means algorithm to cluster and collect the learning behavior data of students into predefined K clusters based on feature similarity. Secondly, this algorithm constructs course quality evaluation indicators from multiple perspectives under the support of multiple evaluation principles. Finally, this algorithm brings together the personal preferences of each decision-maker into a collective preference, allowing these decision-makers to rank the decision-making algorithm by their preference in this paper. Students are regarded as decision-makers, the higher integrated education courses are regarded as decision-making options, the learning behaviors and preferences of students are regarded as attribute decision variables. Thus, the quality evaluation of higher integrated distance education courses can be regarded as a group decision-making process according to the problem description above. This process makes decisions through iterative optimization. Experimental results show that this algorithm performs excellently in the metrics consistency ratio and comprehensive score and has practical application value.

show abstract

Quality evaluation of online courses during COVID-19 pandemic based on integrated FCE-AHP method

Cited by 8 publications

References 36 publications

Effects of the COVID-19 pandemic on architectural education: bibliometric and content analyses

Effects of the COVID-19 pandemic on architectural education: bibliometric and content analyses

Impact of Online Courses on University Student Visual Attention During the COVID-19 Pandemic

Course Quality Evaluation of Higher Integrated Distance Education Based on Group Decision-making Algorithm

Contact Info

Product

Resources

About