Mobile game-based learning as a solution in COVID-19 era: Modeling the pedagogical affordance and student interactions

[1]  Á. Hernández-García,et al.  Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: A case study , 2021, Computers in Human Behavior.

[2]  Mohanaad Shakir,et al.  Impact of Technologies During COVID-19 Pandemic for Improving Behavior Intention to Use E-learning , 2021, Int. J. Interact. Mob. Technol..

[3]  Shajnush Amir,et al.  Facebook’s Social Learning Group for Undergraduate Engineering Courses: A Case Study of Emergency Remote Teaching Amid Large Digital Divide , 2020, 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE).

[4]  YouRu Xie,et al.  The Construction and Effect of the MOOC-based One Plus Three Teaching Model During the COVID-19 Pandemic , 2020, 2020 Ninth International Conference of Educational Innovation through Technology (EITT).

[5]  C. Troussas,et al.  Usability and Educational Affordance of Web 2.0 tools from Teachers’ Perspectives , 2020, PCI.

[6]  Kittiphop Mahawan,et al.  The Effect of Blended Learning with Collaborative Learning upon English Communication Skills of English Teaching Program Students , 2020, 2020 5th International STEM Education Conference (iSTEM-Ed).

[7]  I. Pânișoară,et al.  Motivation and Continuance Intention towards Online Instruction among Teachers during the COVID-19 Pandemic: The Mediating Effect of Burnout and Technostress , 2020, International journal of environmental research and public health.

[8]  Nicoleta Luminita Gudanescu Nicolau,et al.  Sustainability Analysis of the E-Learning Education System during Pandemic Period—COVID-19 in Romania , 2020 .

[9]  Cleo Sgouropoulou,et al.  A Personalized Brain-Based Quiz Game for Improving Students' Cognitive Functions , 2020, BFAL.

[10]  Maria Virvou,et al.  An Enhanced Genetic Algorithm for Heterogeneous Group Formation Based on Multi-Characteristics in Social-Networking-Based Learning , 2020, IEEE Transactions on Learning Technologies.

[11]  Cleo Sgouropoulou,et al.  Ensemble Learning Using Fuzzy Weights to Improve Learning Style Identification for Adapted Instructional Routines , 2020, Entropy.

[12]  Cleo Sgouropoulou,et al.  Applying Genetic Algorithms for Recommending Adequate Competitors in Mobile Game-Based Learning Environments , 2020, ITS.

[13]  Haitao Pu,et al.  Personalized Learning Service Based on Big Data for Education , 2020, 2020 IEEE 2nd International Conference on Computer Science and Educational Informatization (CSEI).

[14]  Mohammed Amin Almaiah,et al.  Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic , 2020, Education and Information Technologies.

[15]  K. Aditya,et al.  Students’ perception and preference for online education in India during COVID -19 pandemic , 2020, Social Sciences & Humanities Open.

[16]  Cleo Sgouropoulou,et al.  Collaboration and fuzzy-modeled personalization for mobile game-based learning in higher education , 2020, Comput. Educ..

[17]  Joke Voogt,et al.  Mobile game-based learning in secondary education: Students' immersion, game activities, team performance and learning outcomes , 2019, Comput. Hum. Behav..

[18]  Gwo-Jen Hwang,et al.  Trends and development in technology-enhanced adaptive/personalized learning: A systematic review of journal publications from 2007 to 2017 , 2019, Comput. Educ..

[19]  Maria Virvou,et al.  SN-Learning: An exploratory study beyond e-learning and evaluation of its applications using EV-SNL framework , 2018, J. Comput. Assist. Learn..

[20]  Hanan Lutfiyya,et al.  Relationship Between Student Engagement and Performance in E-Learning Environment Using Association Rules , 2018, 2018 IEEE World Engineering Education Conference (EDUNINE).

[21]  Jennifer Shewmaker,et al.  Impact of mobile technology on student attitudes, engagement, and learning , 2017, Comput. Educ..

[22]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[23]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[24]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[25]  Manjit Kaur,et al.  Effect of E-learning on public health and environment during COVID-19 lockdown , 2021, Big Data Min. Anal..

[26]  Zheng Yan,et al.  Digital technology use during COVID ‐19 pandemic: A rapid review , 2020 .

[27]  L. Rajabion,et al.  A framework for evaluating the impact of mobile games, technological innovation and collaborative learning on students’ motivation , 2020 .

[28]  Gwo-jen Hwang,et al.  Trends in digital game-based learning in the mobile era: a systematic review of journal publications from 2007 to 2016 , 2019, Int. J. Mob. Learn. Organisation.

[29]  Richard,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace , 2022 .