Online Education (Changing the learning landscape using technology
Allen, I. E., & Seaman, J. (2016). Online Report Card: Tracking online education in the United States. Babson Survey Research Group. Babson College, 231 Forest Street, Babson Park, MA 02457.
Alqurashi, E. (2019). Predicting student satisfaction and perceived learning within online learning environments. Distance Education, 40(1), 133-148.
Alshurideh, M. T., Salloum, S. A., Al Kurdi, B., Monem, A. A., & Shaalan, K. (2019). Understanding the quality determinants that influence the intention to use the mobile learning platforms: A practical study. International Journal of Interactive Mobile Technologies (IJIM), 13(11), 157-183.
Bates, A. W. (2015). Teaching in a digital age. Missouri, MO: University of Missouri.
Bedenlier, S., Bond, M., Buntins, K., Zawacki-Richter, O., & Kerres, M. (2020). Facilitating student engagement through educational technology in higher education: A systematic review in the field of arts and humanities. Australasian Journal of Educational Technology, 126-150.
Bennett, S., Dawson, P., Bearman, M., Molloy, E., & Boud, D. (2017). How technology shapes assessment design: Findings from a study of university teachers. British Journal of Educational Technology, 48(2), 672-682.
Bettinger, E., & Loeb, S. (2017). Promises and pitfalls of online education. Evidence Speaks Reports, 2(15), p1-4.
Blau, G., Jarrell, S., Seeton, A., Young, T., Grace, K., & Hughes, M. (2018). Proposing an expanded measure for comparing online/hybrid to face-to-face courses. Journal of Education and Development, 2(2), 1.
Bose, D., Pakala, K., & Grover, L. (2020). A mobile learning community in a living learning community: perceived impact on digital fluency and communication. The Online Journal of New Horizons in Education-January, 10(1).
Celik, D., & Magoulas, G. D. (2019, September). Challenging the alignment of learning design tools with HE lecturers’ learning design practice. In European Conference on Technology Enhanced Learning (pp. 142-157). Springer, Cham.
Cinquin, P. A., Guitton, P., & Sauzeon, H. (2019). Online e-learning and cognitive disabilities: A systematic review. Computers & Education, 130, 152-167.
Collins, A., & Halverson, R. (2018). Rethinking education in the age of technology: The digital revolution and schooling in America. New York, NY: Teachers College Press.
Crisp, G., Guàrdia, L., & Hillier, M. (2016). Using e-Assessment to enhance student learning and evidence learning outcomes. International Journal of Educational Technology in Higher Education, 18.
Diep, A. N., Zhu, C., Struyven, K., & Blieck, Y. (2017). Who or what contributes to student satisfaction in different blended learning modalities?. British Journal of Educational Technology, 48(2), 473-489.
Drew, C. (2019). Re-examining cognitive tools: New developments, new perspectives, and new opportunities for educational technology research. Australasian Journal of Educational Technology, 35(2).
Ducasse, A. M., & Hill, K. (2019). Developing student feedback literacy using educational technology and the reflective feedback conversation. Practitioner Research in Higher Education, 12(1), 24-37.
Ed on EdTech. (2019). Latest news in education and tech. [website, blog, videos]. https://www.youtube.com/channel/UC4FY5hGOl7pBRqJ_TWDvhVA
EdTech. (2019). EdTech 50 2019. [webpage]. https://edtechnology.co.uk/Article/edtech-50-schools-2019/
El-Henawy, W. M. (2019). Using brain-based instruction to optimize early childhood English language education. In Early childhood development: Concepts, methodologies, tools, and applications (pp. 460-483). Hershey, PA: IGI Global.
Ellis, R. A., & Bliuc, A. M. (2019). Exploring new elements of the student approaches to learning framework: The role of online learning technologies in student learning. Active Learning in Higher Education, 20(1), 11-24.
Engeness, I., & Edwards, A. (2017). The complexity of learning: Exploring the interplay of different mediational means in group learning with digital tools. Scandinavian Journal of Educational Research, 61(6), 650-667.
FitzGerald, E., Kucirkova, N., Jones, A., Cross, S., Ferguson, R., Herodotou, C., … & Scanlon, E. (2018). Dimensions of personalisation in technology‐enhanced learning: A framework and implications for design. British Journal of Educational Technology, 49(1), 165-181.
Fitzgerald, M. S., DellaVecchia, G. P., Palincsar, A. P., & Soloway, E. (2018). Third graders’ use of digital tools designed for multimodal communication in project-based science. International Society of the Learning Sciences, Inc.[ISLS]..
Freeze, R. D., Alshare, K. A., Lane, P. L., & Wen, H. J. (2019). IS success model in e-learning context based on students’ perceptions. Journal of Information systems education, 21(2), 4.
Guerrero, L. Á., García, D. M. A., Pérez, M. A. C., Lira, S. E. T., & de Jesús López Ornelas, E. (2019, September). Learn&safe: digital security to reduce digital gap in educational community. In Proceedings of the IX Latin American Conference on Human Computer Interaction (pp. 1-6).
Haskell, C. (2014). Blowing up the gradebook. [ video ] (17:44 minutes). Blowing up the gradebook – using video games for learning: Chris Haskell at TEDxAmmon
Henriksen, D., Mishra, P., & Fisser, P. (2016). Infusing creativity and technology in 21st century education: A systemic view for change. Educational Technology & Society, 19(3), 27-37.
Howard-Jones, P., Ott, M., van Leeuwen, T., & De Smedt, B. (2015). The potential relevance of cognitive neuroscience for the development and use of technology-enhanced learning. Learning, Media and Technology, 40(2), 131-151.
Huo, Y. (2019). A pedagogy-based framework for optimizing learning efficiency across multiple disciplines in educational games. International Journal of Information and Education Technology, 9(10).
Jabr, F. (2013). The reading brain in the digital age: The science of paper versus screens. Scientific American, 11(04), 2013.
Jack, C., & Higgins, S. (2019). Embedding educational technologies in early years education. Research in Learning Technology.
Kahn, P., Everington, L., Kelm, K., Reid, I., & Watkins, F. (2017). Understanding student engagement in online learning environments: The role of reflexivity. Educational Technology Research and Development, 65(1), 203-218.
Kaimara, P., Poulimenou, S. M., Oikonomou, A., Deliyannis, I., & Plerou, A. (2019). Smartphones at schools? Yes, why not?. European Journal of Engineering Research and Science, 1-6.
Kennedy, M., & Dunn, T. J. (2018). Improving the use of technology enhanced learning environments in higher education in the UK: A qualitative visualization of students’ views. Contemporary Educational Technology, 9(1), 76-89.
Kynigos, C., & Kolovou, A. (2018). Teachers as designers of digital educational resources for creative mathematical thinking. In Research on Mathematics Textbooks and Teachers’ Resources (pp. 145-164). Springer, Cham.
Lamb, R. L., Annetta, L., Firestone, J., & Etopio, E. (2018). A meta-analysis with examination of moderators of student cognition, affect, and learning outcomes while using serious educational games, serious games, and simulations. Computers in Human Behavior, 80, 158-167.
Larmuseau, C., Desmet, P., & Depaepe, F. (2019). Perceptions of instructional quality: impact on acceptance and use of an online learning environment. Interactive Learning Environments, 27(7), 953-964.
Law, K. M., Geng, S., & Li, T. (2019). Student enrollment, motivation and learning performance in a blended learning environment: The mediating effects of social, teaching, and cognitive presence. Computers & Education, 136, 1-12.
Lin, M. H., Chen, H. C., & Liu, K. S. (2017). A study of the effects of digital learning on learning motivation and learning outcome. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 3553-3564.
Lodge, J. M., & Horvath, J. C. (2016). Science of learning and digital learning environments. In J.C. Horvath, .M. Lodge and J. Hattie’s From the laboratory to the classroom: Translating science of learning for teachers.
Lodge, J. M., Kennedy, G., & Lockyer, L. (2016). Brain, mind and educational technology. Australasian Journal of Educational Technology, 32(6).
Ludvigsen, S., & Steier, R. (2019). Reflections and looking ahead for CSCL: digital infrastructures, digital tools, and collaborative learning. International Journal of Computer-Supported Collaborative Learning, 14(4), 415-423.
Macgilchrist, F. (2019). Cruel optimism in edtech: when the digital data practices of educational technology providers inadvertently hinder educational equity. Learning, Media and Technology, 44(1), 77-86.
Mao, J., Ifenthaler, D., Fujimoto, T., Garavaglia, A., & Rossi, P. G. (2019). National policies and educational technology: a synopsis of trends and perspectives from five countries. TechTrends, 63(3), 284-293.
Martin, F., Ritzhaupt, A., Kumar, S., & Budhrani, K. (2019). Award-winning faculty online teaching practices: Course design, assessment and evaluation, and facilitation. The Internet and Higher Education, 42, 34-43.
Mirriahi, N., Liaqat, D., Dawson, S., & Gašević, D. (2016). Uncovering student learning profiles with a video annotation tool: reflective learning with and without instructional norms. Educational Technology Research and Development, 64(6), 1083-1106.
Muir, T., Milthorpe, N., Stone, C., Dyment, J., Freeman, E., & Hopwood, B. (2019). Chronicling engagement: students’ experience of online learning over time. Distance Education, 40(2), 262-277.
Muljana, P. S., & Luo, T. (2019). Factors contributing to student retention in online learning and recommended strategies for improvement: A systematic literature review. Journal of Information Technology Education: Research, 18.
O’Brien, J. (2017). Back to the future of edtech: A meditation. EDUCAUSE. [blog] https://www.educause.edu/interactive/2017/4/back-to-the-future-of-edtech/
Otterborn, A., Schönborn, K., & Hultén, M. (2019). Surveying preschool teachers’ use of digital tablets: general and technology education related findings. International journal of technology and design education, 29(4), 717-737.
Ozernov‐Palchik, O., Norton, E. S., Sideridis, G., Beach, S. D., Wolf, M., Gabrieli, J. D., & Gaab, N. (2017). Longitudinal stability of pre‐reading skill profiles of kindergarten children: implications for early screening and theories of reading. Developmental science, 20(5), e12471.
Pacheco, B. (2018). The rise of the human digital brain: How multidirectional thinking is changing the way we learn. IAP.
Pardo, A., Jovanovic, J., Dawson, S., Gašević, D., & Mirriahi, N. (2019). Using learning analytics to scale the provision of personalised feedback. British Journal of Educational Technology, 50(1), 128-138.
Parsons, D., Inkila, M., & Lynch, J. (2019). Navigating learning worlds: Using digital tools to learn in physical and virtual spaces. Australasian Journal of Educational Technology, 35(4).
Parsons, S. A., Hutchison, A. C., Hall, L. A., Parsons, A. W., Ives, S. T., & Leggett, A. B. (2019). US teachers’ perceptions of online professional development. Teaching and Teacher Education: An International Journal of Research and Studies, 82(1), 33-42.
Parsons, T. D., Lin, L., & Cockerham, D. (Eds.). (2018). Mind, brain and technology: Learning in the age of emerging technologies. Springer.
Pechenkina, E., & Aeschliman, C. (2017). What do students want? Making sense of student preferences in technology-enhanced learning. Contemporary Educational Technology, 8(1), 26-39.
Sandanayake, T. C. (2019). Promoting open educational resources-based blended learning. International Journal of Educational Technology in Higher Education, 16(1), 3.
Soffer, T., & Nachmias, R. (2018). Effectiveness of learning in online academic courses compared with face‐to‐face courses in higher education. Journal of Computer Assisted Learning, 34(5), 534-543.
Study.com (n.d.) Educational technology trends: What teachers should know. Available on https://study.com/academy/lesson/educational-technology-trends-what-teachers-should-know.html
Surabhi, S. (2019). 3 ways machine learning in EdTech is changing the educational industry. Net Solutions. [webpage] https://www.netsolutions.com/insights/machine-learning-in-edtech/
Technology for Every Student? (2:43 minutes) Interview with researcher Todd Rose about digital technology and Universal Design at the Center for Applied Special Technology (CAST).
Uncapher, M. R. (2018). Design considerations for conducting large‐scale learning research using innovative technologies in schools. Mind, Brain, and Education. https://doi.org/10.1111/mbe.12185
Universal Design for Learning (UDL) UDL is a set of principles for curriculum development that give all individuals equal opportunities to learn. UDL provides a blueprint for creating instructional goals, methods, materials, and assessments that work for everyone–not a single, one-size-fits-all solution but rather flexible approaches that can be customized and adjusted for individual needs.
Wilkerson, M. H. (2017). Teachers, students, and after-school professionals as designers of digital tools for learning. In Participatory Design for Learning (pp. 125-138). Routledge.
Williamson, B., Pykett, J., & Nemorin, S. (2018). Biosocial spaces and neurocomputational governance: brain-based and brain-targeted technologies in education. Discourse: Studies in the Cultural Politics of Education, 39(2), 258-275. [Request access from HOLLIS]
Witton, G. (2017). The value of capture: Taking an alternative approach to using lecture capture technologies for increased impact on student learning and engagement. British Journal of Educational Technology, 48(4), 1010-1019.
Xu, H., Liu, S., & Liu, M. (2019). Analysis of the application of modern educational technology in middle school mathematics teaching. International Journal of Innovation and Research in Educational Sciences, 6(3), 2349-5219.
Yen, S. C., Lo, Y., Lee, A., & Enriquez, J. (2018). Learning online, offline, and in-between: comparing student academic outcomes and course satisfaction in face-to-face, online, and blended teaching modalities. Education and Information Technologies, 23(5), 2141-2153.
Zhao, Y., Frey, B., Rice, S., Rury, J. L., & Isaacson, R. (2019). Investigating the Relationship between faculty perception of educational technology and the level of technology integration into teaching and learning (Doctoral dissertation, University of Kansas).
Instructional Design (Creation of Learning Environments)
Al Mamun, M. A., Lawrie, G., & Wright, T. (2020). Instructional design of scaffolded online learning modules for self-directed and inquiry-based learning environments. Computers & Education, 144, 103695.
Alomyan, H., & Green, D. (2019, August). Learning theories: Implications for online learning design. In Proceedings of the 2019 3rd International Conference on E-Society, E-Education and E-Technology (pp. 126-130).
Baldwin, S. J., & Ching, Y. H. (2019). An online course design checklist: development and users’ perceptions. Journal of Computing in Higher Education, 31(1), 156-172.
Holland, A. A. (2019). Effective principles of informal online learning design: A theory-building metasynthesis of qualitative research. Computers & Education, 128, 214-226.
Ou, C., Joyner, D. A., & Goel, A. K. (2019). Designing and developing video lessons for online learning: A seven-principle model. Online Learning, 23(2), 82-104.
Powell, C. G., & Bodur, Y. (2019). Teachers’ perceptions of an online professional development experience: Implications for a design and implementation framework. Teaching and Teacher Education, 77, 19-30.
Suartama, I. K., Setyosari, P., Sulthoni, S., & Ulfa, S. (2019). Development of an instructional design model for mobile blended learning in higher education. International Journal of Emerging Technologies in Learning (iJET), 14(16), 4-22.
Educational Technology (Creation of stand-alone and complementary tools in formal and informal learning)
Angeli, C., Howard, S. K., Ma, J., Yang, J., & Kirschner, P. A. (2017). Data mining in educational technology classroom research: Can it make a contribution?. Computers & Education, 113, 226-242.
Bartolomé, A., Castañeda, L., & Adell, J. (2018). Personalisation in educational technology: the absence of underlying pedagogies. International Journal of Educational Technology in Higher Education, 15(1), 14. [Request access from HOLLIS]
Bateman, B. L. (2019). Internet resources: Educational technology: A guide to resources on the Web. College & Research Libraries News, 64(1), 9-13.
Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., & Kerres, M. (2020). Mapping research in student engagement and educational technology in higher education: a systematic evidence map. International Journal of Educational Technology in Higher Education, 17(1), 2.
Bond, M., Zawacki‐Richter, O., & Nichols, M. (2019). Revisiting five decades of educational technology research: A content and authorship analysis of the British Journal of Educational Technology. British Journal of Educational Technology, 50(1), 12-63.
Brookings Institution. (2013). Education technology: The next generation. [ video ] (1:23:44 minutes). Available on Full Event – Education Technology: The Next Generation
Department of Education, U.S. (2014). Devices. Office of Educational Technology. [ video ] (2:34 minutes). Available on: Department of Education: Devices
Freina, L., & Ott, M. (2015, January). A literature review on immersive virtual reality in education: state of the art and perspectives. In The International Scientific Conference eLearning and Software for Education (Vol. 1, p. 133). Carol I National Defense University.
Gottschalk, F. (2019). Impacts of technology use on children: Exploring literature on the brain, cognition and well-being. Paris: OECD.
Hew, K. F., Lan, M., Tang, Y., Jia, C., & Lo, C. K. (2019). Where is the “theory” within the field of educational technology research?. British Journal of Educational Technology, 50(3), 956-971.
Hollands, F., & Escueta, M. (2019). How research informs educational technology decision-making in higher education: the role of external research versus internal research. Educational Technology Research and Development, 1-18.
Howard, M. C., & Gutworth, M. B. (2020). A meta-analysis of virtual reality training programs for social skill development. Computers & Education, 144, 103707.
Huang, R., Spector, J. M., & Yang, J. (2019). Educational Technology: A primer for the 21st centuary. Springer.
Ifenthaler, D., & Tracey, M. W. (2016). Exploring the relationship of ethics and privacy in learning analytics and design: implications for the field of educational technology. Educational Technology Research and Development, 64(5), 877-880.
Jacobs, K., Leopold, A., Hendricks, D. J., Sampson, E., Nardone, A., Lopez, K. B., … & Dembe, J. (2017). Project career: Perceived benefits of iPad apps among college students with Traumatic Brain Injury (TBI). Work, 58(1), 45-50.
Johnson, P., Anderson, A., & Cammidge, T. (2019). EdTech+ EdTeach: Exploring the Integration of Educational Technology Through Teacher Education. Edited by: Wafa Zoghbor, Suhair Al Alami, & Thomaï Alexiou, 71.
Kickmeier-Rust, M. D., Göbel, S., & Albert, D. (2008, September). 80Days: Melding adaptive educational technology and adaptive and interactive storytelling in digital educational games. In Proceedings of the First International Workshop on Story-Telling and Educational Games (STEG’08).
Lampert, B., Pongracz, A., Sipos, J., Vehrer, A., & Horvath, I. (2018). MaxWhere VR-learning improves effectiveness over clasiccal tools of e-learning. Acta Polytechnica Hungarica, 15(3), 125-147.
Liou, H. H., Yang, S. J., Chen, S. Y., & Tarng, W. (2017). The influences of the 2D image-based augmented reality and virtual reality on student learning. Journal of Educational Technology & Society, 20(3), 110-121.
London School of Economics. (2016). Edtech: The student view on educational technology. [ video ] (2:19 minutes). Available on: Edtech – The student view on educational technology
Maastricht University. (2018). Trend in educational technology. [webpage and videos]. https://library.maastrichtuniversity.nl/trends-in-educational-technology/
Olmos-Raya, E., Ferreira-Cavalcanti, J., Contero, M., Castellanos-Baena, M. C., Chicci-Giglioli, I. A., & Alcañiz, M. (2018). Mobile virtual reality as an educational platform: A pilot study on the impact of immersion and positive emotion induction in the learning process. In Eurasia Journal of Mathematics Science and Technology Education (Vol. 14, No. 6, pp. 2045-2057). Eurasia Publishing House.
Olmos, E., Cavalcanti, J. F., Soler, J. L., Contero, M., & Alcañiz, M. (2018). Mobile virtual reality: A promising technology to change the way we learn and teach. In Mobile and ubiquitous learning (pp. 95-106). Springer, Singapore. [Request access from HOLLIS]
Rankin, J. (2018). Teaching with educational technology. MIT OpenCourseWare. [ video ] (1:07:10 minutes). Available on: 8. Teaching with Educational Technology
Riva, G., Wiederhold, B. K., & Mantovani, F. (2019). Neuroscience of virtual reality: From virtual exposure to embodied medicine. Cyberpsychology, Behavior, and Social Networking, 22(1), 82-96.
Roberts-Mahoney, H., Means, A. J., & Garrison, M. J. (2016). Netflixing human capital development: Personalized learning technology and the corporatization of K-12 education. Journal of Education Policy, 31(4), 405-420.
Sahin, N. T., Abdus-Sabur, R., Keshav, N. U., Liu, R., Salisbury, J. P., & Vahabzadeh, A. (2018). Augmented Reality intervention for social communication in autism in a school classroom: Rated by teachers and parents as effective and usable in a controlled, longitudinal pilot study. https://doi.org/10.31234/osf.io/h2eu8
Sousa, M. J., Cruz, R., & Martins, J. M. (2017). Digital learning methodologies and tools–a literature review. Edulearn17 Proceedings, 5185-5192.
Spector, J. M., Ifenthaler, D., Sampson, D., Yang, J. L., Mukama, E., Warusavitarana, A., … & Bridges, S. (2016). Technology enhanced formative assessment for 21st century learning. Journal of Educational Technology & Society, 19(3), 58-71.
Spencer, K. (2017). The psychology of educational technology and instructional media. Routledge.
Gaming (Use of human thinking algorithms to reinforce learning)
Alstad, Z., Dahlstrom-Hakki, I., Asbell-Clarke, J., Rowe, E., & Altman, M. (2016). The use of multidimensional biopsychological markers to detect learning in educational gaming environments. Working Paper.
Bavelier, D. (2012). Your brain on video games. Ted Talk. [ video ] (17:15 minutes). Available on: https://www.ted.com/talks/daphne_bavelier_your_brain_on_video_games?language=en
Bediou, B., Adams, D. M., Mayer, R. E., Tipton, E., Green, C. S., & Bavelier, D. (2018). Meta-analysis of action video game impact on perceptual, attentional, and cognitive skills. Psychological Bulletin, 144(1), 77.
Burgers, C., Eden, A., van Engelenburg, M. D., & Buningh, S. (2015). How feedback boosts motivation and play in a brain-training game. Computers in Human Behavior, 48, 94-103.
Chalki, P., Tsiara, A., & Mikropoulos, T. A. (2019). An educational neuroscience approach in the design of digital educational games. Themes in eLearning, 12, 17-34.
Charland, P., Allaire-Duquette, G., & Léger, P. M. (2018). Collecting neurophysiological data to investigate users’ cognitive states during game play. GSTF Journal on Computing (JoC), 2(3).
Churchill Club. (2012). Technology in education: How will it change the game? [ video ] (1:30:05 minutes). Available on: 5.7.12 Technology in education: How will it change the game?
Cohen, A. M. (2011). The gamification of education. The Futurist, 45(5), 16.
Cowley, B., Fantato, M., Jennett, C., Ruskov, M., & Ravaja, N. (2014). Learning when serious: Psychophysiological evaluation of a technology-enhanced learning game. Educational Technology & Society, 17(1), 3-16.
Deterding, S. (2012). Gamification: designing for motivation. Interactions, 19(4), 14-17.
Deterding, S., Sicart, M., Nacke, L., O’Hara, K., & Dixon, D. (2011, May). Gamification. using game-design elements in non-gaming contexts. In CHI’11 Extended Abstracts on Human Factors in Computing Systems (pp. 2425-2428). ACM.
Devonshire, I. M., Davis, J., Fairweather, S., Highfield, L., Thaker, C., Walsh, A., … & Hathway, G. J. (2014). Risk-based learning games improve long-term retention of information among school pupils. PloS One, 9(7), e103640.
Domínguez, A., Saenz-De-Navarrete, J., De-Marcos, L., FernáNdez-Sanz, L., PagéS, C., & MartíNez-HerráIz, J. J. (2013). Gamifying learning experiences: Practical implications and outcomes. Computers & Education, 63, 380-392.
Dondlinger, M. J. (2007). Educational video game design: A review of the literature. Journal of Applied Educational Technology, 4(1), 21-31.
Erhel, S., & Jamet, E. (2019). Improving instructions in educational computer games: Exploring the relations between goal specificity, flow experience and learning outcomes. Computers in Human Behavior, 91, 106-114.
Gentry, S. V., Gauthier, A., Ehrstrom, B. L. E., Wortley, D., Lilienthal, A., Car, L. T., … & Car, J. (2019). Serious gaming and gamification education in health professions: systematic review. Journal of medical Internet research, 21(3), e12994.
Hamari, J., Shernoff, D. J., Rowe, E., Coller, B., Asbell-Clarke, J., & Edwards, T. (2016). Challenging games help students learn: An empirical study on engagement, flow and immersion in game-based learning. Computers in human behavior, 54, 170-179.
Hebert, S. (2018). The power of gamification education. [ video ] (18:48 minutes). TedTalk. Available on: The Power of Gamification in Education | Scott Hebert | TEDxUAlberta
Howard-Jones, P. (2013). Minds, brains and learning games at #LEGup. [ video ] (34:57 minutes). Available on: Dr Paul Howard-Jones on Minds, Brains and Learning Games at #LEGup
Howard-Jones, P. (2013). Plenary 3-Minds, brains and learning games.
Howard-Jones, P. A., Jay, T., Mason, A., & Jones, H. (2015). Gamification of learning deactivates the Default Mode Network Frontiers in Psychology, 6.
Kapp, K. M. (2012). The gamification of learning and instruction: game-based methods and strategies for training and education. Hoboken, NJ: John Wiley & Sons.
Kasemsap, K. (2016). Mastering educational computer games, educational video games, and serious games in the digital age. Gamification-Based E-Learning Strategies for Computer Programming Education, 30.
Kim, J. T., & Lee, W. H. (2015). Dynamical model for gamification of learning (DMGL). Multimedia Tools and Applications, 74(19), 8483-8493. [Request access from HOLLIS]
Koivisto, J., & Hamari, J. (2019). The rise of motivational information systems: A review of gamification research. International Journal of Information Management, 45, 191-210
Landers, R. N. (2014). Developing a theory of gamified learning linking serious games and gamification of learning. Simulation & Gaming, 45(6), 752-768.
Nelson, N. J., Fien, H., Doabler, C. T., & Clarke, B. (2016). Considerations for realizing the promise of educational gaming technology. Teaching Exceptional Children, 48(6), 293-300.
Ozcelik, E., Cagiltay, N. E., & Ozcelik, N. S. (2013). The effect of uncertainty on learning in game-like environments. Computers & Education, 67, 12-20.
Pozzi, F., Asensio-Perez, J. I., Ceregini, A., Dagnino, F. M., Dimitriadis, Y., & Earp, J. (2020). Supporting and representing learning design with digital tools: in between guidance and flexibility. Technology, Pedagogy and Education, 1-20.
Pynn, I. L. (2017). School has a bad storyline: Gamification in educational environments. Electronic Theses and Dissertations. 5652. University of Central Florida.
Ronimus, M., Kujala, J., Tolvanen, A., & Lyytinen, H. (2014). Children’s engagement during digital game-based learning of reading: The effects of time, rewards, and challenge. Computers & Education, 71, 237-246.
Sanger, J., Wilson, J., Davies, B., & Whittaker, R. (2019). Young children, videos and computer games: Issues for teachers and parents. Routledge.
Serrano-Laguna, Á., Manero, B., Freire, M., & Fernández-Manjón, B. (2018). A methodology for assessing the effectiveness of serious games and for inferring player learning outcomes. Multimedia Tools and applications, 77(2), 2849-2871.
Shi, L., Cristea, A. I., Hadzidedic, S., & Dervishalidovic, N. (2014, August). Contextual gamification of social interaction–towards increasing motivation in social e-learning. In International Conference on Web-Based Learning (pp. 116-122). Springer International Publishing.
Strickland, H. P., & Kaylor, S. K. (2016). Bringing your a-game: Educational gaming for student success. Nurse Education Today, 40, 101-103.
Thomas, A. (2018). The effective use of game-based education. TedTalk. [ video ] (17:08 minutes). Available on: The Effective Use of Game-Based Learning in Education | Andre Thomas | TEDxTAMU
Trajkovik, V., Malinovski, T., Vasileva-Stojanovska, T., & Vasileva, M. (2018). Traditional games in elementary school: Relationships of student’s personality traits, motivation and experience with learning outcomes. PloS one, 13(8).
Maddison, R., Simons, M., Straker, L., Witherspoon, L., Palmeira, A., & Thin, A. G. (2013). Active video games: An opportunity for enhanced learning and positive health effects?. Cognitive Technology, 18(1), 6-13.
Majuri, J., Koivisto, J., & Hamari, J. (2018). Gamification of education and learning: A review of empirical literature. In Proceedings of the 2nd International GamiFIN Conference, GamiFIN 2018. CEUR-WS.
Mayer, R. E. (2019). Computer games in education. Annual review of psychology, 70, 531-549.
McGonigal, J. (2010). Gaming can make a better world. Ted Talk. [ video ] (19:56 minutes). Available on: https://www.ted.com/talks/jane_mcgonigal_gaming_can_make_a_better_world?language=en
Huizenga, J. C., Ten Dam, G. T. M., Voogt, J. M., & Admiraal, W. F. (2017). Teacher perceptions of the value of game-based learning in secondary education. Computers & Education, 110, 105-115.
Howard-Jones, P. (2012). Neuroscience, games & learning. [ video ] (29:26 minutes). Available on: Dr Paul Howard-Jones – Neuroscience, Games & Learning
Barata, G., Gama, S., Jorge, J., & Gonçalves, D. (2013, October). Improving participation and learning with gamification. In Proceedings of the First International Conference on gameful design, research, and applications (pp. 10-17). ACM.
Haskell, C. (2014). Blowing up the gradebook. [ video ] (17:44 minutes). Blowing up the gradebook – using video games for learning: Chris Haskell at TEDxAmmon
Ahlberg, S. (2018). N. Katherine Hayles, Unthought: The power of the cognitive nonconscious. Chicago and London: University of Chicago Press, 2017. 250 pages. ISBN-13: 978-0-226-44774-2 (cloth); 978-0-226-44788-9 (paper); 978-0-226-44791-9 (e-book). Studia Neophilologica, 90(2), 273-274.
Ahmadi, M., Borcea, C., & Jones, Q. (2019, March). Collaborative lifelogging through the integration of machine and human computation. In Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion (pp. 23-24).
Araujo, T., Helberger, N., Kruikemeier, S., & De Vreese, C. H. (2020). In AI we trust? Perceptions about automated decision-making by artificial intelligence. AI & SOCIETY, 1-13.
Arntz, M., Gregory, T., & Zierahn, U. (2017). Revisiting the risk of automation. Economics Letters, 159, 157-160.
Baker, M. J. (2000). The roles of models in Artificial Intelligence and Education research: a prospective view. Journal of Artificial Intelligence and Education, 11, 122-143..
Bakkar, N., Kovalik, T., Lorenzini, I., Spangler, S., Lacoste, A., Sponaugle, K., … & Bowser, R. (2018). Artificial intelligence in neurodegenerative disease research: use of IBM Watson to identify additional RNA-binding proteins altered in amyotrophic lateral sclerosis. Acta Neuropathologica, 135(2), 227-247.
Bala, B. M. (2019). Artificial Intelligence and its Implications for Future. Artificial Intelligence.
Bellamy, R. K., Dey, K., Hind, M., Hoffman, S. C., Houde, S., Kannan, K., … & Ramamurthy, K. N. (2019). Think your artificial intelligence software is fair? Think again. IEEE Software, 36(4), 76-80.
Bodily, R., Kay, J., Aleven, V., Jivet, I., Davis, D., Xhakaj, F., & Verbert, K. (2018, March). Open learner models and learning analytics dashboards: a systematic review. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 41-50). ACM.
Bundy, A. (2017). Preparing for the future of Artificial Intelligence. Edinburgh Research Explorer.The University of Ediburgh.
Challen, R., Denny, J., Pitt, M., Gompels, L., Edwards, T., & Tsaneva-Atanasova, K. (2019). Artificial intelligence, bias and clinical safety. BMJ Qual Saf, 28(3), 231-237.
Chui, M. (2017). Artificial intelligence the next digital frontier?. McKinsey and Company Global Institute, 47, 3-6.
Cockburn, I. M., Henderson, R., & Stern, S. (2018). The impact of artificial intelligence on innovation (No. w24449). National bureau of economic research.
Conitzer, V. (2019). Designing preferences, beliefs, and identities for artificial intelligence. Durham, NC: Duke University. Association For the Advancement of Artificial Intelligence.
Conitzer, V., Sinnott-Armstrong, W., Borg, J. S., Deng, Y., & Kramer, M. (2017, February). Moral decision making frameworks for artificial intelligence. In Thirty-first aaai conference on artificial intelligence.
Crawford, K. (2016). Artificial intelligence’s white guy problem. The New York Times, 25.
D’Alfonso, S., Santesteban-Echarri, O., Rice, S., Wadley, G., Lederman, R., Miles, C., … & Alvarez-Jimenez, M. (2017). Artificial intelligence-assisted online social therapy for youth mental health. Frontiers in Psychology, 8, 796.
Das, A. K., Ashrafi, A., & Ahmmad, M. (2019, February). Joint cognition of both human and machine for predicting criminal punishment in judicial system. In 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS) (pp. 36-40). IEEE.
Dean, J. (2017). How will artificial intelligence affect your life. [ video ] (15:55 minutes). Available on: How Will Artificial Intelligence Affect Your Life | Jeff Dean | TEDxLA
Deng, L. (2018). Artificial intelligence in the rising wave of deep learning: The historical path and future outlook [perspectives]. IEEE Signal Processing Magazine, 35(1), 180-177.
Deweerdt, S. (2019). Deep connections. Nature, 571(7766), S6-S8.
Dewey, D. (2013). The long-term future of AI (and what we can do about it). Ted Talk. (15:05 minutes)-[ video ]. Available on:The long-term future of AI(and what we can do about it): Daniel Dewey at TEDxVienna (Links to an external site.)Links to an external site.
Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018). From signals to knowledge: A conceptual model for multimodal learning analytics. Journal of Computer Assisted Learning, 34(4), 338-349.
Ding, R. X., Palomares, I., Wang, X., Yang, G. R., Liu, B., Dong, Y., … & Herrera, F. (2020). Large-scale decision-making: characterization, taxonomy, challenges and future directions from an Artificial Intelligence and applications perspective. Information Fusion.
Eaton, E., Koenig, S., Schulz, C., Maurelli, F., Lee, J., Eckroth, J., … & Williams, T. (2018). Blue sky ideas in artificial intelligence education from the EAAI 2017 new and future AI educator program. AI Matters, 3(4), 23-31.
Fazal, M. I., Patel, M. E., Tye, J., & Gupta, Y. (2018). The past, present and future role of artificial intelligence in imaging. European Journal of Radiology, 105, 246-250.
Fiske, A., Henningsen, P., & Buyx, A. (2019). Your robot therapist will see you now: Ethical implications of embodied artificial intelligence in psychiatry, psychology, and psychotherapy. Journal of Medical Internet Research, 21(5), e13216.
Frey, L. (2019). Artificial intelligence and integrated genotype–Phenotype identification. Genes, 10(1), 18.
Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452.
Gil, Y., Honaker, J., Gupta, S., Ma, Y., D’Orazio, V., Garijo, D., … & Jahanshad, N. (2019, March). Towards human-guided machine learning. In Proceedings of the 24th International Conference on Intelligent User Interfaces (pp. 614-624).
Greene, D., Hoffmann, A. L., & Stark, L. (2019, January). Better, nicer, clearer, fairer: A critical Assessment of the movement for ethical artificial intelligence and machine learning. In Proceedings of the 52nd Hawaii International Conference on System Sciences.
Guestrin, C. (2019, October). 4 Systems perspectives into human-centered machine learning. In The 25th Annual International Conference on Mobile Computing and Networking (pp. 1-2).
Hager, G. D., Drobnis, A., Fang, F., Ghani, R., Greenwald, A., Lyons, T., … & Tambe, M. (2019). Artificial intelligence for social good (Links to an external site.)Links to an external site. arXiv preprint arXiv:1901.05406.
Haryanto, E., & Ali, R. M. (2019, January). Students’ attitudes towards the use of artificial intelligence SIRI in EFL learning at one public university. In International Seminar and Annual Meeting BKS-PTN Wilayah Barat (Vol. 1, No. 1).
Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245-258.
Hazard, C. J., Fusting, C., Resnick, M., Auerbach, M., Meehan, M., & Korobov, V. (2019). Natively interpretable machine learning and artificial intelligence: Preliminary results and future directions. arXiv preprint arXiv:1901.00246.
Helbing, D. (2019). Societal, economic, ethical and legal challenges of the digital revolution: from big data to deep learning, artificial intelligence, and manipulative technologies. In Towards Digital Enlightenment (pp. 47-72). Springer, Cham.
Homer, B. D., Ober, T. M., & Plass, J. L. (2018). Digital games as tools for embedded assessment. In A.A: Lipnevich & J.K. Smith’s The Cambridge handbook of instructional feedback, (pp. 357-375). Cambridge University Press.
Hooshyar, D., Ahmad, R. B., Yousefi, M., Fathi, M., Horng, S. J., & Lim, H. (2016). Applying an online game-based formative assessment in a flowchart-based intelligent tutoring system for improving problem-solving skills. Computers & Education, 94, 18-36
Hvizdalova, D. (2018). General artificial intelligence: Making sci-fi a reality. [ video ] (17:32 minutes). TEDTalk. Available on: General Artificial Intelligence: Making sci-fi a reality | Darya Hvizdalova | TEDxTrencin
Jaeger, H. (2016). Artificial intelligence: Deep neural reasoning. Nature, 538(7626), 467.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
Jiang, H., & Nachum, O. (2019). Identifying and correcting label bias in machine learning. arXiv preprint arXiv:1901.04966.
Jo, Y., Cho, H., Lee, S. Y., Choi, G., Kim, G., Min, H. S., & Park, Y. (2019). Quantitative phase imaging and artificial intelligence: A review. IEEE Journal of Selected Topics in Quantum Electronics, 25(1), 1-14.
Johns Hopkins University. (2011, May 13). Artificial grammar reveals inborn language sense, study shows. ScienceDaily. Retrieved February 17, 2020 from www.sciencedaily.com/releases/2011/05/110513112256.htm
Karsenti, T. (2019). Artificial intelligence in education: The urgent need to prepare teachers for tomorrow’s schools. Formation et Profession, 27(1), 112-116.
Katyal, S. K. (2019). Private accountability in the age of artificial intelligence. UCLA Law Review, 66, 54.
Knight, S., Shibani, A., & Shum, S. B. (2018). Augmenting formative writing assessment with learning analytics: A design abstraction approach. In 13th International Conference of the Learning Sciences, London, United Kingdom.
Korteling, J. E., Brouwer, A. M., & Toet, A. (2018). A neural network framework for cognitive bias. Frontiers in psychology, 9, 1561.
Kühl, N., Goutier, M., Hirt, R., & Satzger, G. (2019, January). Machine learning in artificial intelligence: Towards a common understanding. In Proceedings of the 52nd Hawaii International Conference on System Sciences.
Langley, P. (2019, July). An integrative framework for artificial intelligence education. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 9670-9677).
Lapuschkin, S., Wäldchen, S., Binder, A., Montavon, G., Samek, W., & Müller, K. R. (2019). Unmasking Clever Hans predictors and assessing what machines really learn. Nature communications, 10(1), 1096.
Lee, Y. J., & Park, J. Y. (2018). Identification of future signal based on the quantitative and qualitative text mining: a case study on ethical issues in artificial intelligence. Quality & Quantity, 52(2), 653-667.
Liu, M. (2018). The application and development research of artificial intelligence education in wisdom education era. In proceedings of the 2nd International Conference on Social Sciences, Arts and Humanities.
Longo, L. (2018). How to empower education with artificial intelligence (11:31 minutes). [ video ]. Available on: How to Empower Education with Artificial Intelligence | Luca Longo | TEDxDublinInstituteofTechnology (Links to an external site.)Links to an external site.
Longo, L. (2019, October). Empowering qualitative research methods in education with artificial intelligence. In World Conference on Qualitative Research (pp. 1-21). Springer, Cham.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. UK: The Open University.
Lynch, M. (2018). The effects of artificial intelligence on education. [ video ] (7:22 minutes). TEDxTalks. Available on: Effect of Artificial Intelligence on Education | Adrien Dubois | TEDxCanadianIntlSchool
Mamoshina, P., Ojomoko, L., Yanovich, Y., Ostrovski, A., Botezatu, A., Prikhodko, P., … & Ogu, I. O. (2018). Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare. Oncotarget, 9(5), 5665.
Marblestone AH, Wayne G and Kording KP (2016). Toward an integration of deep learning and neuroscience. Frontiers of Computational Neuroscience 10, 94. doi: 10.3389/fncom. 2016.00094
Maseleno, A., Sabani, N., Huda, M., Ahmad, R., Jasmi, K. A., & Basiron, B. (2018). Demystifying learning analytics in personalised learning. International Journal of Engineering & Technology, 7(3), 1124-1129.
Meloney, D. (2015). Artificial intelligence and education. [ video ] (4:09 minutes). Available on: Artificial intelligence and education
Michie, S., Thomas, J., Johnston, M., Mac Aonghusa, P., Shawe-Taylor, J., Kelly, M. P., … & O’Mara-Eves, A. (2017). The human behaviour-change project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation. Implementation Science, 12(1), 121.
Mitchell, T, (2018) Conversational machine learning. Rice Ken Kennedy Institute for Information and Technology. Retrieved: 11/11/2019 https://www.youtube.com/watch? v=NXD0aE8w27g
Moldoveanu, M. C. (2019). Intelligent artificiality: Algorithmic microfoundations for strategic problem solving. Harvard Business School.
Moravčík, M., Schmid, M., Burch, N., Lisý, V., Morrill, D., Bard, N., … & Bowling, M. (2017). Deepstack: Expert-level artificial intelligence in heads-up no-limit poker. Science, 356(6337), 508-513.
Müller, V. C. (Ed.). (2016). Risks of artificial intelligence (p. 291). Boca Raton, FL: CRC Press.
Müller, V. C., & Bostrom, N. (2016). Future progress in artificial intelligence: A survey of expert opinion. In Fundamental issues of artificial intelligence (pp. 555-572). Cham, Switzerland, Springer.
Nalmpantis, C., & Vrakas, D. (2019). Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparasion. Artificial Intelligence Review, 52(1), 217-243.
Nie, N. (2017). Understanding artificial intelligence and its future. [ video ] (16:50 minutes). TEDTalk. Available on: Understanding Artificial Intelligence and Its Future | Neil Nie | TEDxDeerfield
OECD (2019), Artificial Intelligence in Society, OECD Publishing, Paris, https://doi.org/10.1787/eedfee77-en.
Osoba, O. A., & Welser IV, W. (2017). An intelligence in our image: The risks of bias and errors in artificial intelligence. Rand Corporation.
Pasquale, F. (2019). Professional judgment in an era of artificial intelligence and machine learning. boundary 2: an international journal of literature and culture, 46(1), 73-101.
Pearl, J., & Mackenzie, D. (2018). The book of why: the new science of cause and effect. Basic Books.
Perrotta, C., & Williamson, B. (2018). The social life of Learning Analytics: cluster analysis and the ‘performance’ of algorithmic education. Learning, Media and Technology, 43(1), 3-16.
Porayska-Pomsta, K., & Rajendran, G. (2019). Accountability in human and artificial intelligence decision-making as the basis for diversity and educational inclusion. In Artificial Intelligence and Inclusive Education (pp. 39-59). Springer, Singapore.
Reece, B. (July 5, 2018). Voices in AI – Episode 56: A Conversation with Babak Hodjat. [Audio Podcast]. Retreived from https://voicesinai.com/episode/episode-56-a-conversation-with-babak-hodjat/
Riek, L. D. (2016). Robotics technology in mental health care. In Artificial intelligence in behavioral and mental health care(pp. 185-203). Academic Press.
Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582-599.
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited.
Russell, S., Dewey, D., & Tegmark, M. (2015). Research priorities for robust and beneficial artificial intelligence. Ai Magazine, 36(4), 105-114.
Schindlholzer, B. (2016). Artificial intelligence & the future of education systems. Ted Talks. (14: 51 minutes) [ video ]. Available on:Artificial intelligence & the future of education systems | Bernhard Schindlholzer | TEDxFHKufstein (Links to an external site.)Links to an external site.
Shneiderman, B. (2016). Opinion: The dangers of faulty, biased, or malicious algorithms requires independent oversight. Proceedings of the National Academy of Sciences, 113(48), 13538-13540.
Siau, K., & Wang, W. (2018). Building trust in artificial intelligence, machine learning, and robotics. Cutter Business Technology Journal, 31(2), 47-53.
Timms, M. J. (2016). Letting artificial intelligence in education out of the box: educational cobots and smart classrooms. International Journal of Artificial Intelligence in Education, 26(2), 701-712.
Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44.
Tuomi, I. (2018). The impact of artificial intelligence on learning, teaching, and education. (No. JRC113226). Joint Research Centre (Seville site).
Valpola, H. (2018) Can we build human-like AR? Should we? TEDxHelsinki University. [ video ] (15:48 minutes). Available on: Can we build human-like AI? Should we? | Harri Valpola | TEDxHelsinkiUniversity
Vasant, P., & DeMarco, A. (Eds.). (2015). Handbook of research on artificial intelligence techniques and algorithms. Information Science Reference.
Vellido, A. (2019). Societal issues concerning the application of artificial intelligence in medicine. (Links to an external site.)Links to an external site. Kidney Diseases, 5(1), 27-33.
Walsh, C. G., Chaudhry, B., Dua, P., Goodman, K. W., Kaplan, B., Kavuluru, R., … & Subbian, V. (2020). Stigma, biomarkers, and algorithmic bias: recommendations for precision behavioral health with artificial intelligence. JAMIA Open.
Zador, A. M. (2019). A critique of pure learning and what artificial neural networks can learn from animal brains. Nature communications, 10(1), 1-7.
Zaidi, A., Beadle, S., & Hannah, A. (2019). Review of the online learning and artificial intelligence education market: a report for the Department of Education. U.S. Department of Education.
Zecchina, R. (2018). Delving into artificial intelligence. [ video ] (17:26 minutes). Available on: Delving into Artificial Intelligence | Riccardo Zecchina | TEDxBocconiU
Zeitler, A. (2017). The truth behind artificial intelligence. [ video ] (15:36 minutes). TedxTalk. Available on: The Truth Behind Artificial Intelligence | Andrew Zeitler | TEDxStMaryCSSchool
Zhang, Z., Singh, J., Gadiraju, U., & Anand, A. (2019). Dissonance between human and machine understanding. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1-23.