Digital Information Needs for Understanding Cell Divisions in the Human Body
Abstract Information needs for understanding cell divisions in the human body is important in the learning process. Although sketches, images and blocks of 3D puzzles were used for teaching and learning, unfortunately those tools are static and incapable of being manipulated. Hence, digital information is the best tool for the teaching and learning of cell divisions in the human body via software applications. A cell motion is a digital information application developed using leap motion to demonstrate cell movement in the human body. However, the factors that influence students towards adopting this application are not obvious and often ignored. The method for evaluating the factors influencing its user’s acceptance is the Technology Acceptance Model (TAM) via a questionnaire distributed among medical students to gain statistically valid quantitative results through hypothesis-testing. The result indicates that digital information needs for the understanding of cell divisions in the human body are influenced by the user’s Perceived Ease of Use (PEOU) and Perceived Usefulness (PU). However, the Attitude (AT) towards use did have a significant effect on PU and PEOU. Moreover, PEOU had a strong and significant influence on PU, while AT positively influenced users’ behavioural intention (BI) of using digital information needs for the understanding of cell divisions in the human body.
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C. Blazer, “Literature Review Educational Technology”, 2008.
C. Cole, “A Theory of Information Need for Information Retrieval”, J. Am. Soc. Inf. Sci. Technol., vol. 62, no. 7, pp. 1216–1231, 2011.
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D. Healey, “Are Technology-Using Students Better Learners?”, in Teacher to Teacher Conference: The Process of Language Learning, 2001.
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F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology”, MIS Q., vol. 13, no. 3, pp. 319–340, 1989.
Google, “DISCOVER GLASS ENTERPRISE EDITION”, 2020. [Online]. Available: https://www.google.com/glass/start/.
H. Ghuloum, “3D Hologram Technology in Learning Environment”, in Proceedings of Informing Science & IT Education Conference (InSITE), 2010.
H. Harrison, M. Birks, R. Franklin, and J. Mills, “Case study research: Foundations and methodological orientations”, Forum Qual. Soc. Res., vol. 18, no. 1, 2017.
J. T. Fouts, “Research on Computers and Education: Past, Present, and Future”. 2000.
J. Tetnowski, “Qualitative case study research design”, Perspect. Fluen. Fluen. Disord., vol. 25, no. 1, pp. 39–45, 2015.
Kitchenham, B. and L. Pickard, “Case Study for Method and Tool Evaluation”, IEEE Softw., pp. 52-62., 1995.
L. R. N. de Sousa and I. F. Silveira, “A Framework for the Creation of Leap Motion Gestural Interfaces for Handwriting Education to Children with Development Coordination Disorder”, Int. J. Learn. Teach. Educ. Res., vol. 16, no. 4, 2017.
M. Dunleavy, S. Dexter, and W. F. Heinecke, “What added value does a 1:1 student to laptop ratio bring to technology-supported teaching and learning?: Original article”, J. Comput. Assist. Learn., vol. 23, no. 5, pp. 440–452, 2007.
M. Ebner and N. Spot, “Game-Based Learning with the Leap Motion Controller”, in Handbook of Research on Gaming Trends in P-12 Education, no. October, D. Russell and J. M. Laffey, Eds. IGI Global, 2015, pp. 555–565.
M. Honey, K. M. Culp, and R. Spielvogel, “Critical Issue: Using Technology to Improve Student Achievement”. 2005.
M. Johnston, “Using Technology to Enhance New Models of Teaching and Learning”, in The Informed Educator Series., Arlington: Educational Research Service, 2000.
M. S. Abbasi, F. H. Chandio, F. H. Chandio, and F. Shah, “Social influence, voluntariness, experience and the internet acceptance: An extension of technology acceptance model within a south?Asian country context”, J. Enterp. Inf. Manag., vol. 24, no. 1, pp. 30–52, 2011.
O. A. Adjah, “The information needs of female adult literacy learners in Accra”, Inf. Dev., vol. 21, no. 3, pp. 182–192, 2005.
P. A. Guze, “Using Technology to Meet the Challenges of Medical Education”, Trans. Am. Clin. Climatol. Assoc., vol. 126, p. 260?270, 2015.
R. K. Yin, Case Study Research and Applications Design and Methods, 5th ed. Thousand Oaks, CA: Sage, 2014.
R. Sivakumar, “Google glass in education - r. sivakumar”, Conflux J. Eduction, vol. 2, no. 2, pp. 27–31, 2014.
S. Nicola, L. STOICU-TIVADAR, I. Virag, and M. CRI?AN-VIDA, “Leap motion supporting medical education”, in 12th IEEE International Symposium on Electronics and Telecommunications (ISETC), 2016, pp. 1–4.
S. Weerasinghe and M. C. B. Hindagolla, “Technology acceptance model and social network sites (SNS): a selected review of literature”, Glob. Knowledge, Mem. Commun., vol. 67, no. 3, pp. 142–153, 2018.
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V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view”, MIS Q., vol. 27, no. 3, pp. 425–478, 2013.
Y. Gao, “Applying the Technology Acceptance Model (TAM) to Educational Hypermedia: A Field Study”, J. Educ. Multimed. Hypermedia, vol. 14, no. 3, pp. 237–247, 2005.
Y. Hsu and Y. Ching, “Mobile computer-supported collaborative learning: A review of experimental research Yu-Chang Hsu and Yu-Hui Ching”, Br. J. Educ. Technol., vol. 44, no. 5, pp. 2011–2014, 2013.
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“CadaVR The ‘living’ virtual reality cadaver lab.”, 2016. [Online]. Available: https://gallery.leapmotion.com/cadavr/.
“It’s done”, 2019. [Online]. Available: https://www.itsdoneapp.com/.
“Leap Motion Controller Specs—CNET”, 2020.
“Leap Motion Developer”, Ultraleap Ltd, 2020. [Online]. Available: https://developer.leapmotion.com/#101.
Amani Jamal, Asmaa Munshi, Aljojo, N., Talal Qadah, & Azida Zainol. (2020). Digital Information Needs for Understanding Cell Divisions in the Human Body. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 9(2), 5–22. https://doi.org/10.14201/ADCAIJ202092522
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