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Systems
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Information Systems: Discipline, Critical Research and Education
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Information Systems: Discipline, Critical Research and Education

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 6409

Special Issue Editors

Dr. Rasheed Mohammad

E-Mail Website
Guest Editor
College of Computing and Digital Technology, Birmingham City University, Birmingham B4 7XG, UK
Interests: e-learning; sentimental analysis; emotion recognition; statistical analysis; machine learning; AI; healthcare; deep learning
Dr. Faisal Saeed

E-Mail Website
Guest Editor
College of Computing and Digital Technology, Birmingham City University, Birmingham B4 7XG, UK
Interests: data mining; artificial intelligence; machine learning; information retrieval; and health informatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues

Welcome to the Special Issue of Systems titled “Information Systems: Discipline, Critical Research and Education”. Information Systems (ISs) is a multifaceted field intersecting technology, organizations, and human behavior. This Special Issue will delve into the core aspects of IS as a discipline, highlighting critical research that addresses contemporary challenges and advancements within this dynamic domain.

In an era characterized by rapid technological evolution and digital transformation, the role of ISs has never been more pivotal. This Special Issue brings together scholarly contributions that explore theoretical and practical perspectives, offering insights into the development and implementation of robust information systems. By addressing both foundational theories and innovative applications, this Special Issue highlights the significance of IS in driving efficiency, decision-making, and competitive advantage in various organizational contexts.

Moreover, this Special Issue emphasizes the importance of IS education in cultivating the next generation of professionals who will navigate and shape the future of this field. Through critical analyses and case studies, the contributions highlight effective pedagogical approaches and curriculum designs that align with industry needs and academic rigor. Also, the integration of AI in education is underscored, showcasing how AI can enhance learning experiences, personalize education, and prepare students for the evolving demands of the technology-driven world.

We invite researchers to contribute with the diverse articles presented in this Special Issue, which collectively aim to advance the understanding and practice of Information Systems as a vital discipline.

Dr. Rasheed Mohammad
Dr. Faisal Saeed
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ethical AI in education
  • assessment for AI-generated reports
  • AI-generated materials
  • AI readiness by educators
  • AI’s impact on education
  • the future of education processes through co-existence with generative AI

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Published Papers (4 papers)

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Research

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28 pages, 14799 KiB  
Article
Improving Elementary Students’ Geometric Understanding Through Augmented Reality and Its Performance Evaluation
by Wernhuar Tarng, Jen-Kai Huang and Kuo-Liang Ou
Systems 2024, 12(11), 493; https://doi.org/10.3390/systems12110493 - 15 Nov 2024
Viewed by 401
Abstract
Augmented reality (AR) technology provides context-aware experiences by overlaying digital information onto the real world to enhance learning effectiveness and reduce cognitive load. This study aimed to develop an AR Mobile Learning System (ARMLS) to address the limitations of traditional teaching materials and [...] Read more.
Augmented reality (AR) technology provides context-aware experiences by overlaying digital information onto the real world to enhance learning effectiveness and reduce cognitive load. This study aimed to develop an AR Mobile Learning System (ARMLS) to address the limitations of traditional teaching materials and help elementary-school students learn geometric concepts. The ARMLS was designed based on the fifth-grade mathematics curriculum, covering topics such as definitions, geometric properties, different views of prisms and pyramids, and their relationships. A teaching experiment was conducted to compare students’ learning achievement, motivation, and cognitive load when using the ARMLS versus traditional teaching materials. This study adopted a quasi-experimental design, where four fifth-grade classes were selected from an elementary school in northern Taiwan as experimental subjects. A total of 66 students participated in the experiment, divided into two groups: 32 students from two classes as the experimental group (using the ARMLS) and 34 students from the other two classes as the control group (using traditional teaching materials). In the teaching experiment, data were collected through pre-tests, post-tests, and questionnaires. Achievement tests assessed learning effectiveness, while learning motivation and cognitive load were measured with standardized scales. System satisfaction was evaluated using a questionnaire. The Johnson–Neyman method determined the regions of significance in the analysis of covariance. Independent-sample t-tests evaluated differences in learning motivation and cognitive load between the groups, and descriptive statistics summarized system satisfaction responses. The results indicated that (1) the ARMLS enhanced the learning achievement among low- and moderate-achieving students, (2) there was no significant difference in learning motivation between the two groups, (3) the ARMLS helped reduce students’ cognitive load, and (4) most students expressed satisfaction with the ARMLS according to the questionnaire results. The ARMLS enhances engagement and deepens understanding by making abstract geometry topics more accessible. It effectively overcomes the limitations of traditional teaching materials, providing elementary students with an interactive, hands-on approach to learning geometric concepts. Full article
(This article belongs to the Special Issue Information Systems: Discipline, Critical Research and Education)
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24 pages, 892 KiB  
Article
AI-Enabled Multi-Mode Electronic Information Innovation Practice Teaching Reform Prediction and Exploration in Application-Oriented Universities
by Ying Chen, Jianrong Bao, Geqi Weng, Yanhai Shang, Chao Liu and Bin Jiang
Systems 2024, 12(10), 442; https://doi.org/10.3390/systems12100442 - 20 Oct 2024
Viewed by 1081
Abstract
In view of professional learning and practical training in traditional electronic information education of application-oriented universities, this paper constructs electronic information–innovation practice teaching reform (EI-IPTR).In this scheme, by an integrating artificial intelligence (AI)-enabled curriculum with a multi-mode integrated platform and open-style module, big [...] Read more.
In view of professional learning and practical training in traditional electronic information education of application-oriented universities, this paper constructs electronic information–innovation practice teaching reform (EI-IPTR).In this scheme, by an integrating artificial intelligence (AI)-enabled curriculum with a multi-mode integrated platform and open-style module, big data-based comprehensive education resources are optimally configured. We jointly perform the multi-mode construction of innovative practice teaching, professional education stage design, and teaching management improvement, respectively. Subsequently, new practice teaching mechanisms with information technology and its implementation and management methods are established to achieve better teaching effects. It first strengthens learning and intra-group competition to promote students’ innovation in competitions. Then, the AI technique, i.e., attention mechanism-aided long short-term memory (LSTM), is used to model individual students’ abilities. Thus, it accurately evaluates them for teachers to efficiently manage their teaching process in accordance with their aptitude. The teaching reform practice verifies that the AI-enabled big data optimization of teaching reform has a better effect by the above multi-mode innovation. It exhibits an obvious improvement in the quantity and quality of students’ professional knowledge, personal ability, teamwork, and innovative practice. It is also in accordance with the independent completion of practical course teaching in the analysis of big education data. In addition, it realizes high-quality practical teaching by combining multi-mode, multi-level, and open discipline foundations together with efficient, professional skills. Full article
(This article belongs to the Special Issue Information Systems: Discipline, Critical Research and Education)
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15 pages, 599 KiB  
Article
Intuitionistic Linguistic EDAS Method with New Score Function: Case Study on Evaluating Universities’ Innovation and Entrepreneurship Education
by Chunyu Zhao, Haiyang Hou and Hui Yan
Systems 2024, 12(9), 368; https://doi.org/10.3390/systems12090368 - 14 Sep 2024
Viewed by 682
Abstract
Intuitionistic linguistic numbers (ILNs) describe expert evaluation information by representing semantic assessment values and reflecting the confidence level and hesitation of decision-makers. ILNs are widely used to handle uncertain and incomplete information. The Evaluation Based on Distance from Average Solution (EDAS) method selects [...] Read more.
Intuitionistic linguistic numbers (ILNs) describe expert evaluation information by representing semantic assessment values and reflecting the confidence level and hesitation of decision-makers. ILNs are widely used to handle uncertain and incomplete information. The Evaluation Based on Distance from Average Solution (EDAS) method selects the optimal solution based on the distance of each alternative from the average solution, making it suitable for multi-attribute decision-making with conflicting attributes. This study proposes a new scoring function for ILNs and develops an evaluation method combining ILNs with EDAS (IL-EDAS). Experts’ evaluations of each alternative’s indices are expressed using ILNs, and the EDAS method ranks the alternatives to select the optimal solution. We apply this method to assess innovation and entrepreneurship education capabilities in universities, and compare the results with those from other methods to verify their applicability and practicality. Full article
(This article belongs to the Special Issue Information Systems: Discipline, Critical Research and Education)
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Review

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21 pages, 2467 KiB  
Review
Education in Transition: Adapting and Thriving in a Post-COVID World
by Omer S. Alkhnbashi, Rasheed Mohammad and Doaa M. Bamasoud
Systems 2024, 12(10), 402; https://doi.org/10.3390/systems12100402 - 28 Sep 2024
Viewed by 3686
Abstract
The COVID-19 pandemic profoundly disrupted traditional education systems worldwide, prompting a rapid shift to online platforms and the emergence of innovative teaching strategies. This paper critically reviews the extensive body of research on post-COVID-19 education, focusing on the practical and feasible solutions proposed [...] Read more.
The COVID-19 pandemic profoundly disrupted traditional education systems worldwide, prompting a rapid shift to online platforms and the emergence of innovative teaching strategies. This paper critically reviews the extensive body of research on post-COVID-19 education, focusing on the practical and feasible solutions proposed to maintain and enhance educational continuity. The review categorizes and examines studies on various approaches, including simulation-based training, project-based learning, and hybrid models, highlighting their effectiveness during and after the pandemic. Special attention is given to the role of information technology, the challenges faced by educators and students, and the importance of mental health support in the new educational landscape. The findings suggest that while digital tools such as virtual reality and 3D environments show promise, their implementation remains limited, particularly in resource-constrained settings. The study also identifies a significant gap in empirical research on these innovations in the post-pandemic era. Furthermore, the paper highlights the need for systemic changes in curriculum design, educator training, and policy development to address the long-term impacts of the pandemic on education. This review provides a comprehensive overview of the lessons learned from the COVID-19 pandemic, offering insights into how educational institutions can better prepare for future crises. Full article
(This article belongs to the Special Issue Information Systems: Discipline, Critical Research and Education)
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