A Comprehensive Review of Educational Technology on Objective Learning Outcomes in Academic Contexts

Abstract

Rapid advances in technology during the last few decades have provided a multitude of new options for teaching and learning. Although technology is being widely adopted in education, there is a shortage of research on the effects that this technology might have on student learning, and why those effects occur. We conducted a comprehensive review of the literature on various uses of digital technology in educational settings, and the effects of that technology on students’ objective learning outcomes. We interpret these effects within the context of empirical research on effective principles of learning, and the extent to which the affordances of technology permit opportunities for increased engagement with the material, retrieval practice, and spacing. Results revealed that technology is neither beneficial nor harmful for learning when used primarily as a means of presenting information (e.g., information viewed on a computer screen vs. on paper), but can be beneficial when it involves unique affordances that leverage effective learning principles. We discues these findings in light of the ever-increasing availability of technology in education, and the importance of evidence-guided criteria in decisions about adoption and implementation.

This is a preview of subscription content, access via your institution.

Fig. 1

Notes

  1. 1.

    Even with the same instructor across all conditions, there is a possibility that some instructor-related factors could change across conditions or across time (e.g., instructors could improve their teaching effectiveness from one term to the next, or have difficulty implementing a new technology). Notwithstanding these possibilities, instructor-related factors that could influence student learning are likely to be greater when there are different instructors across the conditions (e.g., bringing differences in teaching style, personality, grading practices, or experience), such that the potential influence of these factors was minimized by ensuring that the same instructor taught all students.

  2. 2.

    In these studies it cannot be determined whether the immediacy of the feedback per se was responsible for the learning gains. Some studies have directly explored the timing of feedback and have found that feedback can be more beneficial for learning some types of materials—particularly those involving non-overlapping materials—when it is delayed rather than provided immediately (Carpenter and Vul 2011; Corral et al. in press). In the studies reviewed here, however, the answer to any one item (such as a math problem or grammatical rule) could have informed students’ answers to subsequent problems of the same type. Beyond the timing of feedback per se, therefore, the immediacy of the correct answers could have changed the way that students approached subsequent questions of the same type, increasing the likelihood that they would apply the correct answer.

  3. 3.

    A third group was included that used 3-D printers but did not receive the same type of lecture-based guidance from the instructor. Due to the difference in instructional procedures, this “experiential learning” group is not included in the comparisons.

References

* indicates articles included in the review.

  1. *Anderson, G. R., & Vander Meer, A. W. (1954). A comparative study on the effectiveness of lessons on the slide rule presented via television and in person. The Mathematics Teacher, 47, 323–327.

  2. *Anderson, H. G., Frazier, L., Anderson, S. L., Stanton, R., Gillette, C., Broedel-Zaugg, K., & Yingling, K. (2017). Comparison of pharmaceutical calculations learning outcomes achieved within a traditional lecture or flipped classroom andragogy. American Journal of Pharmaceutical Education, 81,1-9.

  3. *Arias, J. J., Swinton, J., & Anderson, K. (2018). Online vs. face-to-face: A comparison of student outcomes with random assignment. e-Journal of Business Education & Scholarship of Teaching, 12, 1-23.

  4. *Arús, N. A., da Silva, A. M., Duarte, R., da Silveira, P. F., Vizzotto, M. B., da Silveira, H. L. D., & da Silveira, H. E. D. (2017). Teaching dental students to understand the temporomandibular joint using MRI: Comparison of conventional and digital learning methods. Journal of Dental Education, 81, 752-758.

  5. *Baumann-Birkbeck, L., Karaksha, A., Anoopkumar-Dukie, S., Grant, G., Davey, A., Nirthanan, S., & Owen, S. (2015). Benefits of e-learning in chemotherapy pharmacology education. Currents in Pharmacy Teaching & Learning, 7, 106-111.

  6. Benjamin, L. T. (1988). A history of teaching machines. American Psychologist, 43, 703–712.

  7. *Blázquez, B. O., Masluk, B., Gascon, S., Díaz, R. F., Aguilar-Latorre, A., Magallón, I. A., & Botaya, R. M. (2019). The use of flipped classroom as an active learning approach improves academic performance in social work: A randomized trial in a university. PLOS ONE, 14, e0214623.

  8. *Boblick, J. M. (1972). Writing chemical formulas: A comparison of computer assisted instruction with traditional teaching techniques. Science Education, 56, 221-225.

  9. *Bortnik, B., Stozhko, N., Pervukhina, I., Tchernysheva, A., & Belysheva, G. (2017). Effect of virtual analytical chemistry laboratory on enhancing student research skills and practices. Research in Learning Technology, 25, 1-20.

  10. *Botezatu, M., Hult, H., Tessma, M. K., & Fors, U. G. H. (2010). Virtual patient simulation for learning and assessment: Superior results in comparison with regular course exams. Medical Teacher, 32, 845-850.

  11. *Bryner, B. S., Saddawi-Konefka, D., Gest, T. R. (2008). The impact of interactive, computerized educational modules on preclinical medical education. Anatomical Sciences Education, 1, 247-251.

  12. *Cakir, O., & Simsek, N. (2010). A comparative analysis of the effects of computer and paper-based personalization on student achievement. Computers & Education, 55, 1524-1531.

  13. *Campbell, D. L., Peck, D. L., Horn, C. J., & Leigh, R. K. (1987). Comparison of computer-assisted instruction and print drill performance: A research note. Educational Communication & Technology, 35, 95-103.

  14. Carpenter, S. K. (2009). Cue strength as a moderator of the testing effect: The benefits of elaborative retrieval. Journal of Experimental Psychology: Learning, Memory, & Cognition, 35, 1563–1569.

  15. Carpenter, S. K. (2011). Semantic information activated during retrieval contributes to later retention: Support for the mediator effectiveness hypothesis of the testing effect. Journal of Experimental Psychology: Learning, Memory, & Cognition, 37, 1547–1552.

  16. Carpenter, S. K. (2014). Spacing and interleaving of study and practice. In V. A. Benassi, C. E. Overson, & C. M. Hakala (Eds.), Applying the science of learning in education: Infusing psychological science into the curriculum (pp. 131-141). American Psychological Association.

  17. Carpenter, S. K. (2017). Spacing effects in learning and memory. In J. T. Wixted (Ed.), Cognitive psychology of memory, Vol. 2, Learning & memory: A comprehensive reference, 2nd edition, J. H. Byrne (Ed.), pp. 465-485. Oxford: Academic Press.

  18. Carpenter, S. K. (2020). Distributed practice/spacing effect. In L.-f. Zhang (Ed.), Oxford Research Encyclopedia of Education. Oxford University Press.

  19. Carpenter, S. K., & Vul, E. (2011). Delaying feedback by three seconds benefits retention of face-name pairs: The role of active anticipatory processing. Memory & Cognition, 39, 1211–1221.

  20. Carpenter, S. K., Cepeda, N. J., Rohrer, D., Kang, S. H. K., & Pashler, H. (2012). Using spacing to enhance diverse forms of learning: Review of recent research and implications for instruction. Educational Psychology Review, 24, 369–378.

  21. Carpenter, S. K., Rahman, S., & Perkins, K. (2018). The effects of prequestions on classroom learning. Journal of Experimental Psychology: Applied, 24, 34–42.

  22. Cepeda, N. J., Pasher, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132, 354–380.

  23. *Cerra, P. P., González, J. M. S., Parra, B. B., Ortiz, D. R., & Peñín, P. I. A. (2014). Can interactive web-based CAD tools improve the learning of engineering drawing? A case study. Journal of Science Education Technology, 23, 398-411.

  24. *Chang, C.-Y. (2000). Enhancing tenth graders’ earth-science learning through computer-assisted instruction. Journal of Geoscience Education, 48, 636-640.

  25. *Chang, R-C., & Yu, Z-S. (2018). Using augmented reality technologies to enhance students’ engagement and achievement in science laboratories. International Journal of Distance Education Technologies, 16, 54-72.

  26. *Chang, K.-E., Wu, L.-J., Lai, S.-C., & Sung, Y.-T. (2016). Using mobile devices to enhance the interactive learning for spatial geometry. Interactive Learning Environments, 24, 916-934.

  27. *Chen, J. C., Kadlowec, J. A., & Whittinghill, D. C. (2008). Using handheld computers for instantaneous feedback to enhance student learning and promote interaction. International Journal of Engineering Education, 24, 616-624.

  28. Clunie, L., Morris, N. P., Joynes, V. C. T., & Pickering, J. D. (2018). How comprehensive are research studies investigating the efficacy of technology-enhanced learning resources in anatomy education? A systematic review. Anatomical Sciences Education, 11, 303–319.

  29. Corral, D., Carpenter, S. K., Perkins, K., & Gentile, D. A. (2020). Assessing students’ use of optional online lecture reviews. Applied Cognitive Psychology, 34, 318–329.

  30. Corral, D., Carpenter, S. K., & Clingan-Siverly, S. (in press). The effects of immediate versus delayed explanatory feedback on complex concept learning. Quarterly Journal of Experimental Psychology.

  31. Cuban, L. (1986). Teachers and machines: The classroom use of technology since 1920. New York: Teachers College Press.

  32. *Daly, C. J., Bulloch, J. M., Ma, M., & Aidulis, D. (2016). A comparison of animated versus static images in an instructional multimedia presentation. Advances in Physiology Education, 40, 201-205.

  33. *Debevc, M., Weiss, J., Šorgo, A., & Kožuh, I. (2020). Solfeggio learning and the influence of a mobile application based on visual, auditory and tactile modalities. British Journal of Educational Technology, 51, 177-193.

  34. *Delafuente, J. C., Araujo, O. E., & Legg, S. M. (1998). Traditional lecture format compared to computer-assisted instruction in pharmacy calculations. American Journal of Pharmaceutical Education, 62, 62-66.

  35. Delaney, P. F., Verkoeijen, P. P. J. L., & Spirgel, A. (2010). Spacing and testing effects: A deeply critical, lengthy, and at times discursive review of the literature. In B. H. Ross (Ed.), The psychology of learning & motivation: Advances in research & theory (Vol. 53, pp. 63–147). New York: Academic Press.

  36. Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116, 19251–19257.

  37. *Dewhurst, D. G., Hardcastle, J., Hardcastle, P. T., & Stuart, E. (1994). Comparison of a computer simulation program and a traditional laboratory practical class for teaching the principles of intestinal absorption. Educational Experiments, 12, 95-104.

  38. *Diliberto-Macaluso, K., & Hughes, A. (2016). The use of mobile apps to enhance student learning in introduction to psychology. Teaching of Psychology, 43, 48-52.

  39. *Dorji, U., Panjaburee, P., & Srisawasdi, N. (2015). A learning cycle approach to developing educational computer game for improving students’ learning and awareness in electric energy consumption and conservation. Educational Technology & Society, 18, 91-105.

  40. *Du, C. (2011). A comparison of traditional and blended learning in introductory principles of accounting course. American Journal of Business Education, 4, 1-10.

  41. *Ebadi, S., & Ghuchi, K. D. (2018). Investigating the effects of blended learning approach on vocabulary enhancement from EFL learners’ perspective. i-Manager’s Journal on English Language Teaching, 8, 57-68.

  42. *Ebadi, S., & Rahimi, M. (2017). Exploring the impact of online peer-editing using google docs on EFL learners’ academic writing skills: A mixed methods study. Computer Assisted Language Learning, 30, 787-815.

  43. *Ebadi, S., & Rahimi, M. (2018). An exploration into the impact of WebQuest-based classroom on EFL learners’ critical thinking and academic writing skills: A mixed methods study. Computer Assisted Language Learning, 31, 617-651.

  44. Ebbinghaus, H. (1885/1913). Memory (H. A. Ruger, C. E. Bussenius, Transl.). Teachers College, Columbia University, New York.

  45. *Edwards, C. M., Rule, A. C., & Boody, R. M. (2013). Comparison of face-to-face and online mathematics learning of sixth graders. Journal of Computers in Mathematics & Science Teaching, 32, 25-47.

  46. *Ellinger, R. S., & Frankland, P. (1976). Computer-assisted and lecture instruction: A comparative experiment. Journal of Geography, 75, 109-120.

  47. *Englert, C. S., Zhao, Y., Collings, N., & Romig, N. (2005). Learning to read words: The effects of internet-based software on the improvement of reading performance. Remedial & Special Education, 26, 357-371.

  48. *Fajardo-Lira, C., & Heiss, C. (2006). Comparing the effectiveness of a supplemental computer-based food safety tutorial to traditional education in an introductory food science course. Journal of Food Science Education, 5, 31-33.

  49. Fernandez, J., & Jamet, E. (2017). Extending the testing effect to self-regulated learning. Metacognition & Learning, 12, 131–156.

  50. *Francescucci, A., & Foster, M. (2013). The VIRI (virtual, interactive, real-time, instructor-led) classroom: The impact of blended Synchronous online courses on student performance, engagement, and satisfaction. Canadian Journal of Higher Education, 43, 78-91.

  51. *Francescucci, A., & Rohani, L. (2019). Exclusively synchronous online (VIRI) learning: The impact on student performance and engagement outcomes. Journal of Marketing Education, 41, 60-69.

  52. Geller, J., Carpenter, S. K., Lamm, M. H., Rahman, S., Armstrong, P. I., & Coffman, C. R. (2017). Prequestions do not enhance the benefits of retrieval in a STEM classroom. Cognitive Research: Principles & Implications, 2, 42.

  53. Gerbier, E., & Toppino, T. C. (2015). The effect of distributed practice: Neuroscience, cognition, and education. Trends in Neuroscience & Education, 4, 49–59.

  54. *Gibbons, N. J., Evans, C., Payne, A., Shah, K., & Griffin, D. K. (2004). Computer simulations improve university instructional laboratories. Cell Biology Education, 3, 263-269.

  55. *Goh, C. F., & Ong, E. T. (2019). Flipped classroom as an effective approach in enhancing student learning of a pharmacy course with a historically low student pass rate. Currents in Pharmacy Teaching & Learning, 11, 621-629.

  56. Golonka, E. M., Bowles, A. R., Frank, V. M., Richardson, D. L., & Freynik, S. (2014). Technologies for foreign language learning: A review of technology types and their effectiveness. Computer Assisted Language Learning, 27, 70–105.

  57. *González, J. A., Jover, L. Cobo, E., & Muñoz, P. (2010). A web-based learning tool improves student performance in statistics: A randomized masked trial. Computers & Education, 55, 704-713.

  58. Gray, L., Thomas, N., & Lewis, L. (2010). Teachers’ use of educational technology in US public schools: 2009. First look. NCES 2010-040. Washington, DC: National Center for Education Statistics, Institute of Education Sciences, US Department of Education.

  59. Grgurović, M., Chapelle, C. A., & Shelley, M. C. (2013). A meta-analysis of effectiveness studies on computer technology-supported language learning. ReCALL, 25, 165–198.

  60. *Hahn, W., Fairchild, C., & Dowis, W. B. (2013). Online homework managers and intelligent tutoring systems: A study of their impact on student learning in the introductory financial accounting classroom. Issues in Accounting Education, 28, 513-535.

  61. *Harrington, D. (1999). Teaching statistics: A comparison of traditional classroom and programmed instruction/distance learning approaches. Journal of Social Work Education, 35, 343-352.

  62. *Hollerbach, K., & Mims, B. (2007). Choosing wisely: A comparison of online, televised, and face-to-face instructional methods on knowledge acquisition of broadcast audience concepts. Journalism & Mass Communication Educator, 62, 176-189.

  63. *Hsiao, H-S., Chen, J-C., Lin, C-Y., Zhuo, P-W., & Lin, K-Y. (2019). Using 3D printing technology with experiential learning strategies to improve preengineering students’ comprehension of abstract scientific concepts and hands-on ability. Journal of Computer Assisted Learning, 35, 178-187.

  64. *Huang, H.-C. (2014). Online versus paper-based instruction: Comparing two strategy training modules for improving reading comprehension. RELC Journal, 45, 165-180.

  65. *Jeffries, P. R. (2001). Computer versus lecture: A comparison of two methods of teaching oral medication administration in a nursing skills laboratory. Journal of Nursing Education, 40, 323-329.

  66. *Johnson, S. D., Aragon, S. R., Shaik, N., & Palma-Rivas, N. (2000). Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments. Journal of Interactive Learning Research, 11, 29-49.

  67. *Johnson, D., Burnett, M., & Rolling, P. (2002). Comparison of internet and traditional classroom instruction in a consumer economics course. Journal of Family & Consumer Sciences Education, 20, 20-28.

  68. *Karaksha, A., Grant, G., Nirthanan, S. N., Davey, A. K., & Anoopkumar-Dukie, S. (2014). A comparative study to evaluate the educational impact of e-learning tools on Griffith University pharmacy students’ level of understanding using Bloom’s and SOLO taxonomies. Education Research International, 1-11.

  69. Karpicke, J. D. (2017). Retrieval-based learning: A decade of progress. In J. T. Wixted (Ed.), Cognitive psychology of memory, Vol. 2. Learning and memory: A comprehensive reference (J. H. Byrne, Series Ed.), pp. 487-514. Oxford: Academic Press.

  70. *Kiliçkaya, F. (2015). Computer-based grammar instruction in an EFL context: Improving the effectiveness of teaching adverbial clauses. Computer Assisted Language Learning, 28, 325-340.

  71. Kirkwood, A., & Price, L. (2013). Missing: Evidence of a scholarly approach to teaching and learning with technology in higher education. Teaching in Higher Education, 18, 327–337.

  72. Kirkwood, A., & Price, L. (2014). Technology-enhanced learning and teaching in higher education: What is ‘enhanced’ and how do we know? A critical literature review. Learning, Media, & Technology, 39, 6–36.

  73. Kornell, N., & Vaughn, K. E. (2016). How retrieval attempts affect learning: A review and synthesis. Psychology of Learning & Motivation, 65, 183–215.

  74. Kuepper-Tetzel, C. E. (2014). Strong effects on weak theoretical grounds: Understanding the distributed practice effect. Zeitschrift für Psychologie, 222, 71–81.

  75. *Kühl, T., & Münzer, S. (2019). The moderating role of additional information when learning with animations compared to static pictures. Instructional Science, 47, 659-677.

  76. *Kunnath, B., & Kriek, J. (2018). Exploring effective pedagogies using computer simulations to improve grade 12 learners’ understanding of the photoelectric effect. African Journal of Research in Mathematics, Science & Technology Education, 22, 329-339.

  77. *Lancellotti, M., Thomas, S., & Kohli, C. (2016). Online video modules for improvement in student learning. Journal of Education for Business, 91, 19-22.

  78. Lee, S. W.-Y., & Tsai, C.-C. (2013). Technology-supported learning in secondary and undergraduate biological education: Observations from literature review. Journal of Science Education & Technology, 22, 226–233.

  79. *Lee, C. S. C., Rutecki, G. W., Whittier, F. C., Clarett, M. R., & Jarjoura, D. (1997). A comparison of interactive computerized medical education software with a more traditional teaching format. Teaching & Learning in Medicine, 9, 111-115.

  80. *Lents, N. H., & Cifuentes, O. E. (2009). Web-based learning enhancements: Video lectures through voice-over powerpoint in a majors-level biology course. Journal of College Science Teaching, 39, 38-46.

  81. *Lewis, J. L. (2015). A comparison between two different activities for teaching learning principles: Virtual animal labs versus human demonstrations. Scholarship of Teaching & Learning in Psychology, 1, 182-188.

  82. Li, Q., & Ma, X. (2010). A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educational Psychology Review, 22, 215–243.

  83. *Li, J-T., & Tong, F. (2019). Multimedia-assisted self-learning materials: The benefits of E-flashcards for vocabulary learning in Chinese as a foreign language. Reading & Writing, 32, 1175-1195.

  84. *Lin, Y-T. (2019). Impacts of a flipped classroom with a smart learning diagnosis system on students’ learning performance, perception, and problem solving ability in a software engineering course. Computers in Human Behavior, 95, 187-196.

  85. Little, J. L., & McDaniel, M. A. (2015). Metamemory monitoring and control following retrieval practice for text. Memory & Cognition, 43, 85–98.

  86. *Liu, H.-C., & Su, I.-H. (2011). Learning residential electrical wiring through computer simulation: The impact of computer-based learning environments on student achievement and cognitive load. British Journal of Educational Technology, 42, 598-607.

  87. *Liu, T.-C., Lin, Y.-C., & Kinshuk. (2010). The application of simulation-assisted learning statistics (SALS) for correcting misconceptions and improving understanding of correlation. Journal of Computer Assisted Learning, 26, 143-158.

  88. *Liu, K-P, Tai, S-J. D., & Liu, C-C. (2018). Enhancing language learning through creation: The effect of digital storytelling on student learning motivation and performance in a school English course. Educational Technology Research & Development, 66, 913-935.

  89. *Lucchetti, A. L. G., Ezequiel, O. D. S., de Oliveira, I. N., Moreira-Almeida, A., & Lucchetti, G. (2018). Using traditional or flipped classrooms to teach “Geriatrics and Gerontology?” Investigating the impact of active learning on medical students’ competencies. Medical Teacher, 40, 1248-1256.

  90. Lui, A. K.-F., Poon, M. H. M., & Wong, R. M. H. (2019). Automated generators of examples and problems for studying computer algorithms. Interactive Technology & Smart Education, 16, 204–218.

  91. *MacLaughlin, E. J., Supernaw, R. B., & Howard, K. A. (2004). Impact of distance learning using videoconferencing technology on student performance. American Journal of Pharmaceutical Education, 68, 58.

  92. *Mathiowetz, V., Yu, C.-H., & Quake-Rapp, C. (2016). Comparison of a gross anatomy laboratory to online anatomy software for teaching anatomy. Anatomical Sciences Education, 9, 52–59.

  93. Mayer, R. E., & Moreno, R. (2002). Animation as an aid to multimedia learning. Educational Psychology Review, 14, 87–99.

  94. *McClean, P., Johnson, C., Rogers, R., Daniels, L., Reber, J., Slator, B. M., Terpstra, J., & White, A. (2005). Molecular and cellular biology animations: Development and impact on student learning. Cell Biology Education, 4, 169-175.

  95. McDaniel, M. A., Agarwal, P. K., Huelser, B. J., McDermott, K. B., & Roediger III, H. L. (2011). Test-enhanced learning in a middle school science classroom: The effects of quiz frequency and placement. Journal of Educational Psychology, 103, 399–414.

  96. *McDonough, M., & Marks, I. M. (2002). Teaching medical students exposure therapy for phobia/panic – randomized, controlled comparison of face-to-face tutorial in small groups vs. solo computer instruction. Medical Education, 36, 412-417.

  97. *McLaughlin, J. E., & Rhoney, D. H. (2015). Comparison of an interactive e-learning preparatory tool and a conventional downloadable handout used within a flipped neurologic pharmacotherapy lecture. Currents in Pharmacy Teaching & Learning, 7, 12-19.

  98. *Mešić, V., Dervić, D., Gazibegović-Busuladžić, A., & Salibašić, D. (2015). Comparing the impact of dynamic and static media on students’ learning of one-dimensional kinematics. Eurasia Journal of Mathematics, Science & Technology Education, 11, 1119-1140.

  99. *Nguyen, D. M., & Kulm, G. (2005). Using web-based practice to enhance mathematics learning and achievement. Journal of Interactive Online Learning, 100 1-16.

  100. *Nguyen, J., & Paschal, C. B. (2002). Development of online ultrasound instructional module and comparison to traditional teaching methods. Journal of Engineering Education, 91, 275-283.

  101. *Nikou, S. A., & Economides, A. A. (2018). Mobile-based micro-learning and assessment: Impact on learning performance and motivation of high school students. Journal of Computer Assisted Learning, 34, 269-278.

  102. Nora, A., & Snyder, B. P. (2008). Technology and higher education: The impact of e-learning approaches on student academic achievement, perceptions and persistence. Journal of College Student Retention: Research, Theory & Practice, 10, 3–19.

  103. *Nouri, J., Cerratto-Pargman, T., Rossitto, C., & Ramberg, R. (2014). Learning with or without mobile devices? A comparison of traditional school fieldtrips and inquiry-based mobile learning activities. Research & Practice in Technology Enhanced Education, 9, 241-262.

  104. *Oglesbee, T. W., Bitner, L. N., & Wright, G. B. (1988). Measurement of incremental benefits in computer enhanced instruction. Issues in Accounting Education, 3, 365-377.

  105. *Olkun, S. (2003). Comparing computer versus concrete manipulatives in learning 2D geometry. Journal of Computers in Mathematics & Science Teaching, 22, 43-56.

  106. *Pei, X., Jin, Y., Zheng, T., & Zhao, J. (2020). Longitudinal effect of a technology-enhanced learning environment on sixth-grade students’ science learning: The role of reflection. International Journal of Science Education, 42, 271-289.

  107. *Perry, J. L., Cunningham, L. D., Gamage, J. K., & Kuehn, D. P. (2011). Do 3D stereoscopic computer animations improve student learning of surgical procedures? International Journal of Instructional Media, 38, 369-378.

  108. Pressey, S. L. (1926). A simple apparatus which gives tests and scores—and teaches. School & Society, 23, 373–376.

  109. Pressey, S. L. (1927). A machine for automatic teaching of drill material. School & Society, 25, 549–552.

  110. Price, L., & Kirkwood, A. (2014). Using technology for teaching and learning in higher education: A critical review of the role of evidence in informing practice. Higher Education Research & Development, 33, 549–564.

  111. Rawson, K. A., & Dunlosky, J. (2011). Optimizing schedules of retrieval practice for durable and efficient learning: How much is enough? Journal of Experimental Psychology: General, 140, 283–302.

  112. Roediger III, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15, 20–27.

  113. Roediger III, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17, 249–255.

  114. Rohrer, D. (2015). Student instruction should be distributed over long time periods. Educational Psychology Review, 27, 635–643.

  115. Rosen, Y., & Salomon, G. (2007). The differential learning achievements of constructivist technology-intensive learning environments as compared with traditional ones: A meta-analysis. Journal of Educational Computing Research, 36, 1–14.

  116. Schacter, J., & Fagnano, C. (1999). Does computer technology improve student learning and achievement? How, when, and under what conditions? Journal of Educational Computing Research, 20, 329–343.

  117. *Schoenfeld-Tacher, R., McConnell, S., & Graham, M. (2001). Do no harm—A comparison of the effects of on-line vs. traditional delivery media on a science course. Journal of Science Education & Technology, 10, 257-265.

  118. *Shadiev, R., Hwang, W-Y., & Liu, T-Y. (2018). Investigating the effectiveness of a learning activity supported by a mobile multimedia learning system to enhance autonomous EFL learning in authentic contexts. Educational Technology Research & Development, 66, 893-912.

  119. *Siciliano, P. C., Jenks, M. A., Dana, M. N., & Talbert, B. A. (2011). The impact of audio technology on undergraduate instruction in a study abroad course on English gardens. NACTA Journal, 55, 46-53.

  120. Skinner, B. F. (1958). Teaching machines. Science, 128, 969–977.

  121. *Spichtig, A. N., Gehsmann, K. M., Pascoe, J. P., & Ferrara, J. D. (2019). The impact of adaptive, web-based, scaffolded silent reading instruction on the reading achievement of students in grades 4 and 5. The Elementary School Journal, 119, 443-467.

  122. *Steinweg, S. B., Davis, M. L., & Thomson, W. S. (2005). A comparison of traditional and online instruction in an introduction to special education course. Teacher Education & Special Education, 28, 62-73.

  123. *Su, C.-H., & Cheng, C.-H. (2014). A mobile gamification learning system for improving the learning motivation and achievements. Journal of Computer Assisted Learning, 31, 268-286.

  124. Swenson, P. W., & Evans, M. (2003). Hybrid courses as learning communities. In S. Reisman (Ed.), Electronic learning communities issues and practices (pp. 27–72). Greenwich, CT: Information Age Publishing.

  125. Thalheimer, W., & Cook, S. (2019). How to calculate effect sizes from published research articles: A simplified methodology. Retrieved September 3, 2019 from http://work-learning.com/effect_sizes.htm.

  126. *Tilidetzke, R. (1992). A comparison of CAI and traditional instruction in a college algebra course. Journal of Computers in Mathematics & Science Teaching, 11, 53-62.

  127. *Turan, Z., Meral, E., & Sahin, I. F. (2018). The impact of mobile augmented reality in geography education: Achievements, cognitive loads and views of university students. Journal of Geography in Higher Education, 42, 427-441.

  128. *Verdugo, D. R., & Belmonte, I. A. (2007). Using digital stories to improve listening comprehension with Spanish young learners of English. Language Learning & Technology, 11, 87-101.

  129. *Vichitvejpaisal, P., Sitthikongsak, S., Preechakoon, B., Kraiprasit, K., Parakkamodom, S., Manon, C., & Petcharatana, S. (2001). Does computer-assisted instruction really help to improve the learning process? Medical Education, 35, 983-989.

  130. *Wang, S., & Sleeman, P. J. (1993). A comparison of the relative effectiveness of computer-assisted instruction and conventional methods for teaching an operations management course in a school of business. International Journal of Instructional Media, 20, 225-234.

  131. *Wiebe, J. H., & Martin, N. J. (1994). The impact of a computer-based adventure game on achievement and attitudes in geography. Journal of Computing in Childhood Education, 5, 61-71.

  132. *Wiesner, T. F., & Lan, W. (2004). Comparison of student learning in physical and simulated unit operations experiments. Journal of Engineering Education, 93, 195-204.

  133. *William, A., Vidal, V. L., & John, P. (2016). Traditional instruction versus virtual reality simulation: A comparative study of phlebotomy training among nursing students in Kuwait. Journal of Education & Practice, 7, 18-25.

  134. *Wu, T-T. (2018). Improving the effectiveness of English vocabulary review by integrating ARCS with mobile game-based learning. Journal of Computer Assisted Learning, 34, 315-323.

  135. *Yarahmadzehi, N., & Goodarzi, M. (2020). Investigating the role of formative mobile based assessment in vocabulary learning of pre-intermediate EFL learners in comparison with paper based assessment. Turkish Online Journal of Distance Education, 21, 181-196.

  136. *Yildirim, Z., Ozden, M. Y., & Aksu, M. (2001). Comparison of hypermedia learning and traditional instruction on knowledge acquisition and retention. The Journal of Educational Research, 94, 207-214.

  137. *Zaini, A., & Mazdayasna, G. (2015). The impact of computer-based instruction on the development of EFL learners’ writing skills. Journal of Computer Assisted Learning, 31, 516-528.

  138. *Zubas, P., Heiss, C., & Pedersen, M. (2006). Comparing the effectiveness of a supplemental online tutorial to traditional instruction with nutritional science students. Journal of Interactive Online Learning, 5, 75-81.

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Shana K. Carpenter.

Ethics declarations

Conflict of Interest

Shana Carpenter has received grants from the National Science Foundation (DUE 1504480) and the James S. McDonnell Foundation (220020483).

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This material is based upon work supported by the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition, Collaborative Grant No. 220020483. We thank Sierra Lauber, Luke Huber, and Kyle St. Hilaire for their help in locating articles.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yeung, K.L., Carpenter, S.K. & Corral, D. A Comprehensive Review of Educational Technology on Objective Learning Outcomes in Academic Contexts. Educ Psychol Rev (2021). https://doi.org/10.1007/s10648-020-09592-4

Download citation

Keywords

  • Technology
  • Learning
  • Classroom
  • Cognitive Science
  • Effective Learning Principles