Design of a mobile-based learning management system for incorporating employment demands: Case context of an Australian University

Singh, Harpreet; Miah, Shah Jahan

doi:10.1007/s10639-018-9816-1

Cited by 19 publications

(6 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Li and Xue (2021) agreed that introducing international academic peer review and tenure tracking mechanisms into China's current higher education system was necessary to achieve the international educational standards pursued by world-class universities, especially in a fiercely global competitive environment [ 4 ]. Singh and Miah (2019) thought that research on mobile applications in education by technologies such as mobile learning was still in its infancy, and formal methods for deep learning management systems to support students and scholars to meet industry needs were still to be developed by higher education institutions [ 5 ]. Lv et al (2020) made an effort to find a cognitive computing technology to effectively learn and process large-scale data considering massive data generated with the continuous expansion of data scale [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Employment Quality Evaluation Model of Application-Oriented University Graduates by Deep Learning

Zhang

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

In view of the employment difficulties of college graduates, this paper analyzes the overflow of graduates in a particular period caused by the expansion of enrollment in various colleges and universities and the social phenomenon of social positions in short supply. First, the employment status of application-oriented college students and the deficiencies of employment guidance courses are summarized. Then, deep learning technology is combined with the relevant employment concept to construct an employment training model to guide college students in employment. Besides, a questionnaire on learning effect and employment quality is designed from four perspectives: learning motivation, concentration, teaching process, and final results. The information collected through the questionnaire demonstrates that the employment quality and learning effect of male and female students are not significantly affected by gender differences. In addition, the P values of learning motivation, concentration, and teaching process are all less than 0.01, and the unstandardized coefficient of the teaching process is 0.349, which has the most significant impact on the learning effect. In short, the three factors positively affect the learning effect. Therefore, it comes to the conclusion of improving the ability and strategy of classroom employment guidance. If one wants to be successful in job hunting and career selection, it is not enough just to be competitive but also to be good at it. Being good at the competition is reflected in having good psychological quality, strength, and a good competitive state. In the job hunting and career selection competition, attention should be paid to whether the expected value is appropriate. College students should have sufficient self-awareness before preparing to submit resumes. During the interview, they should overcome emotional anxiety. If a person can treat study, work, and life in a good mood from beginning to end, he will win the competition. The research reported here can provide some reference suggestions for the employment quality of application-oriented college graduates.

show abstract

Section: Introductionmentioning

confidence: 99%

Exploring the Employment Quality Evaluation Model of Application-Oriented University Graduates by Deep Learning

Zhang

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Previous literature used DSR for designing and evaluating solution artifacts for stakeholders such as Singh and Miah [ 48 ], who argue that big data management and data analytics are the critical aspects of a design artifact. Moreover, Miah et al [ 32 , 38 ] utilized DSR to design and develop their People Tracker artifact, which is based on other design studies [ 32 , 34 , 38 ], Miah et al [ 33 ], Miah et al [ 35 ]).…”

Section: Design Science Research Methodologymentioning

confidence: 99%

A design concept of big data analytics model for managers in hospitality industries

Mousavian

Miah

Zhong

2023

Pers Ubiquit Comput

Self Cite

View full text Add to dashboard Cite

“…al. (34) have used the DSR framework to design a mobile based application for education; Carstensena and Bernhard (35) designed and improved teaching in the engineering education sector by utilizing the DSR methodology; Miah et. al.…”

Section: Integrated Design Science Research Methodologymentioning

confidence: 99%

Designing and Evaluating a Big Data Analytics Approach for predicting students’ success factors

Fahd

Miah

2022

Preprint

View full text Add to dashboard Cite

Reducing student attrition in tertiary education plays a significant role in the core mission and financial well-being of an educational institution. The availability of big data source from Learning Management System (LMS) can be analysed to help with the attrition issues. This study aims to use an integrated Design science research (DSR) methodology to develop and evaluate a Big Data Analytical Solution (BDAS) embedded in Educational Decision Support System as an educational artefact. The BDAS as DSR artefact harnesses the outcome of the application of Artificial Intelligence(AI) based approaches on the dataset collected from student interaction with LMS to train a predictive model to predict potential students at risk. Identifying students at risk helps to take timely intervention in the learning process to improve student academic progress to increase the retention rate. To evaluate the performance of the predictive model, we compare the accuracy of the collection of representational Artificial Intelligence algorithms in the literature. The BDAS aims not to replace any existing practice but to support educators to implement a variety of pedagogical practices to improve students’ academic performance.

show abstract

Design of a mobile-based learning management system for incorporating employment demands: Case context of an Australian University

Cited by 19 publications

References 38 publications

Exploring the Employment Quality Evaluation Model of Application-Oriented University Graduates by Deep Learning

Exploring the Employment Quality Evaluation Model of Application-Oriented University Graduates by Deep Learning

A design concept of big data analytics model for managers in hospitality industries

Designing and Evaluating a Big Data Analytics Approach for predicting students’ success factors

Contact Info

Product

Resources

About