Student Engagement with Technology-Enhanced Resources in Mathematics in Higher Education: A Review
Abstract
:1. Introduction
- RA1: student engagement with technology in higher education (and mathematics).
- RA2: technology in education and in mathematics in higher education: what works and what does not.
- RA3: evaluating the use of technology in higher education (and mathematics) and the use of frameworks and models.
2. Materials and Methods
3. Student Engagement with Technology in Higher Education (and Mathematics)
- What is meant by student engagement with technology and why is it important?
- In what way(s) has student engagement with technology been measured?
- What are the factors of implementations that encourage/discourage student engagement with technology?
3.1. What Is Meant by Student Engagement with Technology and Why Is It Important?
Because there has been considerable research on how students behave, feel, and think, the attempt to conceptualize and examine portions of the literature under the label “engagement” is potentially problematic; it can result in a proliferation of constructs, definitions, and measures of concepts that differ slightly, thereby doing little to improve conceptual clarity [37] (p. 60).
- Behavioural engagement is generally defined in three ways: positive conduct (following rules and guidelines), involvement in learning tasks (effort and persistence), and participation in school-related activities.
- Emotional engagement refers to students’ affective responses in the classroom such as being bored, sad, anxious, etc., but also students’ sense of belonging.
- Cognitive engagement is derived from an investment in learning and self-regulation and being strategic when learning [37] (pp. 62–63).
‘The time and energy students devote to educationally sound activities inside and outside of the classroom, and the policies and practices that institutions use to induce students to take part in these activities.’ [29] (p. 25).
Student engagement is the energy and effort that students employ within their learning community, observable via any number of behavioural, cognitive or affective indicators across a continuum. It is shaped by a range of structural and internal influences, including the complex interplay of relationships, learning activities and the learning environment [36] (p. 3).
3.2. In What Ways Has Student Engagement with Technology Been Measured?
3.3. What Are the Factors of Implementations That Encourage/Discourage Student Engagement with Technology?
3.4. Discussion on Student Engagement
4. Technology in Education and in Mathematics in Higher Education: What Works and What Does Not
- What is meant by technology-enhanced resources in undergraduate mathematics education?
- What are the benefits of using technology-enhanced resources in first-year undergraduate mathematics modules?
- What factors of the technology-enhanced resource implementations impacted on the associated benefits?
4.1. What Is Meant by Technology-Enhanced Resources in Undergraduate Mathematics Education?
4.2. What Are the Benefits of Using Technology-Enhanced Resources in Undergraduate Mathematics Modules?
4.3. What Factors of the Technology-Enhanced Resource Implementations Impacted on the Associated Benefits?
4.4. Discussion from the Literature on Technology-Enhanced Resource Use in Mathematics Education
5. Evaluating Technology Use in Higher Education (and Mathematics) and the Use of Frameworks and Models
- How have the uses of technology-enhanced resources been measured?
- What models or frameworks are available to classify and evaluate technology-enhanced resource implementations?
- What features of technology integrations are described/classified within these models and frameworks?
5.1. How Have the Uses of Technology-Enhanced Resources Been Measured?
5.2. What Models or Frameworks Are Available to Classify and Evaluate Technology-Enhanced Resource Implementations?
- Technology integration—these frameworks refer to how technology is integrated into teaching and learning.
- Theoretical frameworks—these are used to examine how learning occurs using technology.
- Technology affordances and types—these frameworks categorise different technologies according to functionality or affordances the technology supports.
- User experience frameworks—these refer to how technology is examined from the user’s, or student’s in this case, perspective.
5.3. What Features of Technology Integrations Are Described/Classified within These Models and Frameworks?
5.3.1. Mathematics Specific Frameworks
Pedagogical Opportunities
Didactical Functions
Instrumental Orchestration
Didactic Tetrahedron
Categories of Tools
Classification System of Research Studies
- Technology which describes the type of technology in use. They used a refinement of the Hoyles and Noss (as cited in [74] (p. 261)) categorisation of tools (described above), which also took into account the types of technology use observed in the literature review. There were seven final classifications within the technology type.
- Learning theory. Studies were classified according to whether they adopted a Behaviourist, cognitive, constructivist, social constructivist, or constructionist teaching and learning approach.
- Technology adoption. They used the SAMR model to describe how technology is integrated, because it pertains to the level of technology adoption specific to tasks and activities. This model will be discussed in more detail below.
- Purpose. Each of the studies was classified based on the aim of the study: for example, to change students’ mathematical attitude, improve performance, or engender collaboration and discussion.
Formative Assessment in Science and Mathematics Education
- Agents (student, peers, and teacher) that intervene in formative assessment processes in the classroom and that can activate formative assessment strategies.
- Strategies for formative assessment activated by the agents, based on the work of Wiliam and Thompson [152].
- Functionalities of technology within the formative assessment processes: sending and displaying; processing and analysing; and providing an interactive environment [126].
Mobile Apps Classifications
Framework for Engagement in Mathematics (FEM)
5.3.2. General Frameworks of Relevance
Substitution Augmentation Modification Redefinition (SAMR) Model
Technological Pedagogical Content Knowledge (TPACK)
SAMR vs. TPACK
User Experience Models
Universal Design for Learning (UDL)
- Representation, to provide learners with various ways of acquiring information and knowledge;
- Expression, to provide learners with alternatives for demonstrating what they know;
- Engagement to tap into learners’ interests, challenge them appropriately, and motivate them to learn.
5.4. Discussion on Evaluations and Frameworks/Models in Higher Education
6. Conclusions and Contributions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
- Bayne, S. What’s the matter with “technology enhanced learning”? Learn. Media Technol. 2014, 40, 5–20. [Google Scholar] [CrossRef]
- Selwyn, N. Looking beyond learning: Notes towards the critical study of educational technology. J. Comput. Assist. Learn. 2010, 26, 65–73. [Google Scholar] [CrossRef]
- Fredricks, J.A.; Wang, M.-T.; Schall Linn, J.; Hofkens, T.L.; Sung, H.; Parr, A.; Allerton, J. Using qualitative methods to develop a survey measure of math and science engagement. Learn. Instr. 2016, 43, 5–15. [Google Scholar] [CrossRef]
- Kahu, E.R.; Nelson, K. Student engagement in the educational interface: Understanding the mechanisms of student success. High. Educ. Res. Dev. 2018, 37, 58–71. [Google Scholar] [CrossRef]
- Trowler, V. Student Engagement Literature Review; Higher Education Academy: York, UK, 2010; Available online: https://www.advance-he.ac.uk/knowledge-hub/student-engagement-literature-review (accessed on 15 November 2022).
- Beer, C.; Clark, K.; Jones, D. Indicators of engagement. In Proceedings of the Sydney 2010 Ascilite Conference, Sydney, Australia, 5–8 December 2010; pp. 75–86. [Google Scholar]
- Bond, M.; Bedenlier, S. Facilitating Student Engagement Through Educational Technology: Towards a Conceptual Framework. J. Interact. Media Educ. 2019, 1, 1–14. [Google Scholar] [CrossRef]
- Kahu, E.R. Framing student engagement in higher education. Stud. High. Educ. 2013, 38, 758–773. [Google Scholar] [CrossRef]
- Zepke, N.; Leach, L. Beyond hard outcomes: ‘Soft’ outcomes and engagement as student success. Teach. High. Educ. 2010, 15, 661–673. [Google Scholar] [CrossRef]
- Drijvers, P. Evidence for benefit? Reviewing empirical research on the use of digital tools in mathematics education. In Proceedings of the 13th International Congress on Mathematical Education, Hamburg, Germany, 24–31 July 2016. [Google Scholar]
- Drijvers, P. Digital Technology in Mathematics Education: Why It Works (Or Doesn’t). In Selected Regular Lectures from the 12th International Congress on Mathematical Education; Cho, S.J., Ed.; Springer: Cham, Switzerland, 2015; pp. 135–151. [Google Scholar] [CrossRef]
- King, M.; Dawson, R.; Batmaz, F.; Rothberg, S. The need for evidence innovation in educational technology evaluation. In Proceedings of the INSPIRE XIX: Global Issues in IT Education, Southampton, UK, 15 April 2014; pp. 9–23. [Google Scholar]
- Bray, A.; Tangney, B. Mathematics, technology interventions and pedagogy—Seeing the wood from the trees. In Proceedings of the 5th International Conference on Computer Supported Education, Aachen, Germany, 6–8 May 2013; pp. 57–63. [Google Scholar] [CrossRef]
- Geiger, V.; Calder, N.; Tan, H.; Loong, E.; Miller, J.; Larkin, K. Transformations of teaching and learning through digital technologies. In Research in Mathematics Education in Australasia 2012–2015; Makar, K., Dole, S., Visnovska, J., Goos, M., Bennison, A., Fry, K., Eds.; Springer: Singapore, 2016; pp. 255–280. [Google Scholar] [CrossRef] [Green Version]
- Pierce, R.; Stacey, K. Mapping Pedagogical Opportunities Provided by Mathematics Analysis Software by mathematics analysis software. Int. J. Comput. Math. Learn. 2010, 15, 1–20. [Google Scholar] [CrossRef]
- Henrie, C.R.; Halverson, L.R.; Graham, C.R. Measuring student engagement in technology-mediated learning: A review. Comput. Educ. 2015, 90, 36–53. [Google Scholar] [CrossRef]
- Boote, D.N.; Beile, P. Scholars Before Researchers: On the Centrality of the Dissertation Literature Review in Research Preparation. Educ. Res. 2005, 34, 3–15. [Google Scholar] [CrossRef]
- Hart, C. Doing a Literature Review: Releasing the Social Science Research Imagination; Sage Publishing: London, UK, 1999. [Google Scholar]
- Randolph, J.J. A guide to writing the dissertation literature review. Prac. Assess. Res. Eval. 2009, 14, 13. [Google Scholar] [CrossRef]
- Franz, T. Hawthorne Effect. In The SAGE Encyclopaedia of Educational Research, Measurement, and Evaluation; Frey, B.B., Ed.; SAGE Publications, Inc.: Thousand Oaks, CA, USA, 2018; pp. 767–769. [Google Scholar] [CrossRef]
- Hochberg, K.; Kuhn, J.; Müller, A. Using smartphones as experimental tools—Effects on interest, curiosity, and learning in physics education. J. Sci. Educ. Technol. 2018, 27, 385–403. [Google Scholar] [CrossRef]
- Constantine, N.A. Publication Bias. In Encyclopedia of Epidemiology; Boslaugh, S., Ed.; SAGE Publications: Thousand Oaks, CA, USA, 2012; pp. 854–855. [Google Scholar] [CrossRef]
- Baker, J.D. The Purpose, Process, and Methods of Writing a Literature Review. AORN J. 2016, 103, 265–269. [Google Scholar] [CrossRef]
- Grant, M.J.; Booth, A. A typology of reviews: An analysis of 14 review types and associated methodologies. Health Inf. Libr. J. 2009, 26, 91–108. [Google Scholar] [CrossRef]
- Onwuegbuzie, A.J.; Frels, R. Seven Steps to a Comprehensive Literature Review: A Multimodal and Cultural Approach, 1st ed.; SAGE Publications: London, UK, 2016. [Google Scholar]
- Petticrew, M.; Roberts, H. Systematic Reviews in the Social Sciences: A Practical Guide; Blackwell Publishing: Hoboken, NJ, USA, 2006. [Google Scholar] [CrossRef]
- Buteau, C.; Marshall, N.; Jarvis, D.; Lavicza, Z. Integrating Computer Algebra Systems in Post-Secondary Mathematics Education: Preliminary Results of a Literature Review. Int. J. Technol. Math. Educ. 2010, 17, 57–68. [Google Scholar]
- Lavicza, Z. Integrating technology into mathematics teaching at the university level. ZDM—Int. J. Math. Educ. 2010, 42, 105–119. [Google Scholar] [CrossRef]
- Kuh, G.D. What We’re Learning About Student Engagement From NSSE: Benchmarks for Effective Educational Practices. Change Mag. High. Learn. 2003, 35, 24–32. [Google Scholar] [CrossRef]
- Schindler, L.A.; Burkholder, G.J.; Morad, O.A.; Marsh, C. Computer-based technology and student engagement: A critical review of the literature. Int. J. Educ. Technol. High. Educ. 2017, 14, 1–28. [Google Scholar] [CrossRef]
- Sinatra, G.M.; Heddy, B.C.; Lombardi, D. The Challenges of Defining and Measuring Student Engagement in Science. Educ. Psychol. 2015, 50, 1–13. [Google Scholar] [CrossRef]
- Henderson, M.; Selwyn, N.; Aston, R. What works and why? Student perceptions of “useful” digital technology in university teaching and learning. Stud. High. Educ. 2015, 42, 1567–1579. [Google Scholar] [CrossRef]
- Coupland, M.; Dunn, P.K.; Galligan, L.; Oates, G.; Trenholm, S. Tertiary mathematics education. In Research in Mathematics Education in Australasia 2012–2015; Maka, K., Dole, S., Visnovska, J., Goos, M., Bennison, A., Fry, K., Eds.; Springer: Singapore, 2016; pp. 187–211. [Google Scholar] [CrossRef]
- O’Flaherty, J.; Phillips, C. The use of flipped classrooms in higher education: A scoping review. Internet High. Educ. 2015, 25, 85–95. [Google Scholar] [CrossRef]
- OECD. Students, Computers and Learning; Making the Connection; OECD Publishing: Paris, France, 2015. [Google Scholar] [CrossRef]
- Bond, M.; Buntins, K.; Bedenlier, S.; Zawacki-Richter, O.; Kerres, M. Mapping research in student engagement and educational technology in higher education: A systematic evidence map. Int. J. Educ. Technol. High. Educ. 2020, 17, 1–30. [Google Scholar] [CrossRef]
- Fredricks, J.A.; Blumenfeld, P.C.; Paris, A.H. School Engagement: Potential of the Concept, State of the Evidence. Rev. Educ. Res. 2004, 74, 59–109. [Google Scholar] [CrossRef] [Green Version]
- Astin, A.W. Student involvement: A developmental theory for higher education. J. Coll. Stud. Dev. 1984, 25, 518–529. [Google Scholar]
- Coates, H. A model of online and general campus-based student engagement. Assess. Eval. High. Educ. 2007, 32, 121–141. [Google Scholar] [CrossRef]
- Reeve, J.; Tseng, C.-M. Agency as a fourth aspect of students’ engagement during learning activities. Contemp. Educ. Psychol. 2011, 36, 257–267. [Google Scholar] [CrossRef]
- O’Brien, H.L.; Toms, E.G. The development and evaluation of a survey to measure user engagement. J. Am. Soc. Inf. Sci. Technol. 2010, 61, 50–69. [Google Scholar] [CrossRef]
- Coates, H. The value of student engagement for higher education quality assurance. Qual. High. Educ. 2005, 11, 25–36. [Google Scholar] [CrossRef]
- Bedenlier, S.; Bond, M.; Buntins, K.; Zawacki-Richter, O.; Kerres, M. Learning by Doing? Reflections on Conducting a Systematic Review in the Field of Educational Technology. In Systematic Reviews in Educational Research; Zawacki-Richter, O., Kerres, M., Bedenlier, S., Bond, M., Buntins, K., Eds.; Springer: Wiesbaden, Germany, 2020; pp. 111–127. [Google Scholar] [CrossRef]
- Yang, D.; Lavonen, J.M.; Niemi, H. Online learning engagement: Critical factors and research evidence from literature. Themes Sci. Technol. Educ. 2018, 11, 1–22. [Google Scholar]
- O’Brien, H.L.; Toms, E.G. What is User Engagement? A Conceptual Framework for Defining User Engagement with Technology. J. Am. Soc. Inf. Sci. Technol. 2008, 59, 938–955. [Google Scholar] [CrossRef]
- Fabian, K.; Topping, K.J.; Barron, I.G. Using mobile technologies for mathematics: Effects on student attitudes and achievement. Educ. Technol. Res. Dev. 2018, 66, 1119–1139. [Google Scholar] [CrossRef]
- Lake, E.; Nardi, E. Looking for Goldin: Can adopting student engagement structures reveal engagement structures for teachers? In Proceedings of the Joint Meeting of PME 38 and the PME-NA 36, Vancouver, BC, Canada, 15–20 July 2014; Volume 4, pp. 49–56. [Google Scholar]
- Oates, G.; Sheryn, L.; Thomas, M.O.J. Technology-active student engagement in an undergraduate mathematics course. In Proceedings of the Joint Meeting of PME 38 and the PME-NA 36, Vancouver, BC, Canada, 15–20 July 2014; Volume 4, pp. 329–336. [Google Scholar]
- Pierce, R.; Stacey, K.; Barkatsas, A. A scale for monitoring students’ attitudes to learning mathematics with technology. Comput. Educ. 2007, 48, 285–300. [Google Scholar] [CrossRef]
- Steen-Utheim, A.T.; Foldnes, N. A qualitative investigation of student engagement in a flipped classroom. Teach. High. Educ. 2018, 23, 307–324. [Google Scholar] [CrossRef]
- Trenholm, S.; Hajek, B.; Robinson, C.L.; Chinnappan, M.; Albrecht, A.; Ashman, H. Investigating undergraduate mathematics learners’ cognitive engagement with recorded lecture videos. Int. J. Math. Educ. Sci. Technol. 2019, 50, 3–24. [Google Scholar] [CrossRef] [Green Version]
- Helme, S.; Clarke, D. Identifying cognitive engagement in the mathematics classroom. Math. Educ. Res. J. 2001, 13, 133–153. [Google Scholar] [CrossRef]
- Hong-Meng Tai, J.; Bellingham, R.; Lang, J.; Dawson, P. Student perspectives of engagement in learning in contemporary and digital contexts. High. Edu. Res. Dev. 2019, 38, 1075–1089. [Google Scholar] [CrossRef]
- Mirriahi, N.; Jovanovic, J.; Dawson, S.; Gašević, D.; Pardo, A. Identifying engagement patterns with video annotation activities: A case study in professional development. Australas. J. Educ. Technol. 2018, 34, 57–72. [Google Scholar] [CrossRef]
- Thomas, M.O.J.; Hong, Y.Y.; Oates, G. Innovative Uses of Digital Technology in Undergraduate Mathematics. In Innovation and Technology Enhancing Mathematics Education: Perspectives in the Digital Era; Faggiano, E., Ferrara, F., Montone, A., Eds.; Springer: Cham, Switzerland, 2017; pp. 109–136. [Google Scholar] [CrossRef]
- Galligan, L.; McDonald, C.; Hobohm, C. Conceptualising, implementing and evaluating the use of digital technologies to enhance mathematical understanding: Reflections on an innovation-development cycle. In Educational Developments, Practices and Effectiveness; Lock, J., Redmond, P., Danaher, P.A., Eds.; Palgrave Macmillan: London, UK, 2015; pp. 137–160. [Google Scholar]
- Kanwal, S. Exploring Affordances of an Online Environment: A Case-Study of Electronics Engineering Undergraduate Students’ Activity in Mathematics. Int. J. Res. Undergrad. Math. Educ. 2020, 6, 42–64. [Google Scholar] [CrossRef]
- Whitton, N.; Moseley, A. Deconstructing Engagement: Rethinking Involvement in Learning. Simul. Gaming 2014, 45, 433–449. [Google Scholar] [CrossRef]
- Henrie, C.R.; Bodily, R.; Manwaring, K.C.; Graham, C.R. Exploring intensive longitudinal measures of student engagement in blended learning. Int. Rev. Res. Open Distrib. Learn. 2015, 16, 131–155. [Google Scholar] [CrossRef]
- Fredricks, J.A.; McCloskey, W. The measurement of student engagement: A comparatve anallysis of various methods and student self report instruments. In Handbook of Research on Student Engagement; Christenson, S.L., Reschly, A.L., Wylie, C., Eds.; Springer: Boston, MA, USA, 2012; pp. 763–782. [Google Scholar] [CrossRef]
- Bulger, M.E.; Mayer, R.E.; Almeroth, K.C.; Blau, S.D. Measuring Learner Engagement in Computer-Equipped College Classrooms. J. Educ. Mult. Hyper. 2008, 17, 129–143. [Google Scholar]
- Beatson, N.; Gabriel, C.-A.; Howell, A.; Scott, S.; Van Der Meer, J.; Wood, L.C. Just opt in: How choosing to engage with technology impacts business students’ academic performance. J. Account. Educ. 2019, 50, 100641. [Google Scholar] [CrossRef]
- Cruz-Benito, J.; Therón, R.; García-Peñalvo, F.J.; Pizarro Lucas, E. Discovering usage behaviors and engagement in an Educational Virtual World. Comput. Hum. Behav. 2015, 47, 18–25. [Google Scholar] [CrossRef]
- Al-Sakkaf, A.; Omar, M.; Ahmad, M. A systematic literature review of student engagement in software visualization: A theoretical perspective. Comput. Sci. Educ. 2019, 29, 283–309. [Google Scholar] [CrossRef]
- McMullen, S.; Oates, G.; Thomas, M.O.J. An integrated technology course at university: Orchestration and mediation. In Proceedings of the 39th Conference of the International Group for the Psychology of Mathematics Education, Hobart, Australia, 13–18 July 2015; Volume 1, pp. 249–257. [Google Scholar]
- Pardos, Z.A.; Baker, R.S.J.; San Pedro, M.; Gowda, S.M.; Gowda, S.M. Affective States and State Tests: Investigating How Affect and Engagement during the School Year Predict End-of-Year Learning Outcomes. J. Learn. Anal. 2014, 1, 107–128. [Google Scholar] [CrossRef]
- Attard, C.; Holmes, K. “It gives you that sense of hope”: An exploration of technology use to mediate student engagement with mathematics. Heliyon 2020, 6, e02945. [Google Scholar] [CrossRef]
- Lai, C.; Wang, Q.; Lei, J. What factors predict undergraduate students’ use of technology for learning? A case from Hong Kong. Comput. Educ. 2012, 59, 569–579. [Google Scholar] [CrossRef]
- Anastasakis, M.; Robinson, C.L.; Lerman, S. Links between students’ goals and their choice of educational resources in undergraduate mathematics. Teach. Math. Applic. 2017, 36, 67–80. [Google Scholar] [CrossRef]
- Conole, G.; Alevizou, P. A Literature Review of the Use of Web 2.0 Tools in Higher Education Table of Contents; Higher Education Academy: York, UK, 2010. [Google Scholar]
- Englund, C.; Olofsson, A.D.; Price, L. Teaching with technology in higher education: Understanding conceptual change and development in practice. High. Educ. Res. Dev. 2017, 36, 73–87. [Google Scholar] [CrossRef]
- Price, L.; Kirkwood, A. Enhancing Professional Learning and Teaching through Technology: A Synthesis of Evidence-Based Practice among Teachers in Higher Education; Higher Education Academy: York, UK, 2011; Available online: http://oro.open.ac.uk/30686/ (accessed on 15 November 2022).
- Selwyn, N. Editorial: In praise of pessimism-the need for negativity in educational technology. Br. J. Educ. Technol. 2011, 42, 713–718. [Google Scholar] [CrossRef]
- Bray, A.; Tangney, B. Technology usage in mathematics education research—A systematic review of recent trends. Comput. Educ. 2017, 114, 255–273. [Google Scholar] [CrossRef]
- Oates, G. Technology in Mathematics Education: A Stocktake & Crystal-Ball Gazing. In Proceedings of the Asian Technology Conference in Mathematics (ATCM) 2016: Teaching and Learning Mathematics, Science and Engineering through Technology, Pattaya, Thailand, 14–18 December 2016; pp. 1–17. Available online: https://atcm.mathandtech.org/EP2016/invited.html (accessed on 15 November 2022).
- Conole, G.; de Laat, M.; Dillon, T.; Darby, J. “Disruptive technologies”, “pedagogical innovation”: What’s new? Findings from an in-depth study of students’ use and perception of technology. Comput. Educ. 2008, 50, 511–524. [Google Scholar] [CrossRef]
- Oliver, M. Technological determinism in educational technology research: Some alternative ways of thinking about the relationship between learning and technology. J. Comput. Assist. Learn. 2011, 27, 373–384. [Google Scholar] [CrossRef] [Green Version]
- Selwyn, N. Sharpening the ‘ed-tech imagination’: Improving academic research in education and technology. In Proceedings of the Critical Perspectives of Learning with New Media, Melbourne, Australia, 23 March 2012; pp. 6–16. [Google Scholar]
- Drijvers, P. Head in the clouds, feet on the ground—A realistic view on using digital tools in mathematics education. In Vielfältige Zugänge zum Mathematikunterricht; Büchter, A., Glade, M., Herold-Blasius, R., Klinger, M., Schacht, F., Scherer, P., Eds.; Springer Spektrum: Wiesbaden, Germany, 2019; pp. 163–176. [Google Scholar] [CrossRef]
- Jarvis, D.; Buteau, C.; Doran, C.; Novoseltsev, A. Innovative CAS Technology Use in University Mathematics Teaching and Assessment: Findings from a Case Study in Alberta, Canada. J. Comput. Math. Sci. Teach. 2018, 37, 309–354. [Google Scholar]
- Drijvers, P. Empirical Evidence for Benefit? Reviewing Quantitative Research on the Use of Digital Tools in Mathematics Education. In Uses of Technology in Primary and Secondary Mathematics Education; Ball, L., Drijvers, P., Ladel, S., Siller, H.-S., Tabach, M., Vale, C., Eds.; Springer: Cham, Switzerland, 2018; pp. 161–175. [Google Scholar] [CrossRef]
- Ronau, R.N.; Rakes, C.R.; Bush, S.B.; Driskell, S.O.; Niess, M.L.; Pugalee, D.K. A Survey of Mathematics Education Technology Dissertation Scope and Quality: 1968–2009. Am. Educ. Res. J. 2014, 51, 974–1006. [Google Scholar] [CrossRef]
- Kirkwood, A.; Price, L. Technology-enhanced learning and teaching in higher education: What is “enhanced” and how do we know? A critical literature review. Learn. Media. Technol. 2014, 39, 6–36. [Google Scholar] [CrossRef]
- Higher Education Funding Council for England. Enhancing Learning and Teaching through the Use of Technology. 2009. Available online: https://dera.ioe.ac.uk/140/1/09_12.pdf (accessed on 15 November 2022).
- National Forum for the Enhancement of Teaching and Learning in Higher Education. National Survey on the Use of Technology to Enhance Teaching and Learning in Higher Education 2014 National Forum. 2015. Available online: https://www.teachingandlearning.ie/publication/national-survey-on-the-use-of-technology-to-enhance-teaching-and-learning-in-higher-education-2014/ (accessed on 15 November 2022).
- Dimitriadis, Y.; Goodyear, P. Forward-oriented design for learning: Illustrating the approach. Res. Learn. Technol. 2013, 21, 1–13. [Google Scholar] [CrossRef]
- Conole, G. Designing for Learning in an Open World; Springer: New York, NY, USA, 2013. [Google Scholar]
- Goodyear, P. Teaching as design. HERDSA Rev. High. Educ. 2015, 2, 27–50. Available online: http://www.herdsa.org.au/wp-content/uploads/HERDSARHE2015v02p27.pdf (accessed on 15 November 2022).
- Laurillard, D. Teaching as a Design Science: Building Pedagogical Patterns for Learning and Technology; Routledge: London, UK, 2012. [Google Scholar]
- Allen, M.; Sites, R. Leaving ADDIE for SAM: An Agile Model for Developing the Best Learning, 1st ed.; American Society for Training and Development: Alexandria, VA, USA, 2012. [Google Scholar]
- Branch, R.M.; Kopcha, T.J. Instructional design models. In Handbook of Research on Educational Communications and Technology, 4th ed.; Spector, J., Merrill, M., Elen, J., Bishop, M., Eds.; Springer,: New York, NY, USA, 2014; pp. 77–87. [Google Scholar] [CrossRef]
- Dousay, T. Instructional Design Models. In Foundations of Learning and Instructional Design Technology, 1st ed.; West, R.E., Ed.; Pressbooks: Montreal, QC, Canada, 2018; Available online: https://lidtfoundations.pressbooks.com (accessed on 15 November 2022).
- Monaghan, J.; Trouche, L.; Borwein, J.M. Tools and Mathematics Instruments for Learning; Springer: Cham, Switzerland, 2016. [Google Scholar]
- Trenholm, S.; Alcock, L.; Robinson, C.L. An investigation of assessment and feedback practices in fully asynchronous online undergraduate mathematics courses. Int. J. Math. Educ. Sci. Technol. 2015, 46, 1197–1221. [Google Scholar] [CrossRef]
- Trgalová, J.; Clark-Wilson, A.; Weigand, H.-G. Technology and resources in mathematics education. In Developing Research in Mathematics Education, 1st ed.; Dreyfus, T., Artigue, M., Potari, D., Prediger, S., Ruthven, K., Eds.; Routledge: London, UK, 2018; pp. 142–161. Available online: https://www.taylorfrancis.com/chapters/technology-resources-mathematics-education-jana-trgalová-alison-clark-wilson-hans-georg-weigand/e/10.4324/9781315113562-12 (accessed on 29 November 2022).
- Kurz, T.L.; Middleton, J.A.; Yanik, H.B. A Taxonomy of Software for Mathematics Instruction. Contemp. Iss. Technol. Teach. Educ. 2005, 5, 123–137. [Google Scholar]
- Jupri, A.; Drijvers, P.; Van den Heuvel-Panhuizen, M. An instrumentation theory view on students’ use of an Applet for Algebraic substitution. Int. J. Technol. Math. Educ. 2016, 23, 63–80. [Google Scholar] [CrossRef]
- Ratnayake, I.; Oates, G.; Thomas, M.O.J. Supporting Teachers Developing Mathematical Tasks with Digital Technology. In Proceedings of the 39th annual conference of the Mathematics Education Research Group of Australasia, Adelaide, Australia, 3–7 July 2016; pp. 543–551. [Google Scholar]
- Trouche, L.; Drijvers, P. Webbing and orchestration. Two interrelated views on digital tools in mathematics education. Teach. Math. Applic. 2014, 33, 193–209. [Google Scholar] [CrossRef]
- Loch, B.; Gill, O.; Croft, T. Complementing mathematics support with online MathsCasts. ANZIAM J. 2012, 53, C561–C575. [Google Scholar] [CrossRef] [Green Version]
- Robinson, M.; Loch, B.; Croft, T. Student Perceptions of Screencast Feedback on Mathematics Assessment. Int. J. Res. Undergrad. Math. Educ. 2015, 1, 363–385. [Google Scholar] [CrossRef]
- Triantafyllou, E.; Timcenko, O.; Student, O.T. Student perceptions on learning with online resources in a flipped mathematics classroom. In Proceedings of the Ninth Congress of the European Society for Research in Mathematics Education, Prague, Czech Republic, 4–8 February 2015; pp. 2573–2579. [Google Scholar]
- King, S.O.; Robinson, C.L. Formative Teaching: A Conversational Framework for Evaluating the Impact of Response Technology on Student Experience, Engagement and Achievement. In Proceedings of the 2009 39th IEEE Frontiers in Education Conference, San Antonio, TX, USA, 18–21 October 2009; pp. 1–6. [Google Scholar] [CrossRef]
- Lee, J. An Exploratory Study of Effective Online Learning: Assessing Satisfaction Levels of Graduate Students of Mathematics Education Associated with Human and Design Factors of an Online Course. Int. Rev. Res. Open Distrib. Learn. 2014, 15, 111–132. [Google Scholar] [CrossRef]
- Trenholm, S.; Alcock, L.; Robinson, C.L. Mathematics lecturing in the digital age. Int. J. Math. Educ. Sci. Technol. 2012, 43, 703–716. [Google Scholar] [CrossRef]
- Gibson, J. The theory of affordances. In Perceiving, Acting, and Knowing; Shaw, R., Bransford, J., Eds.; Laurence Erlbaum: Hillsdale, NJ, USA, 1977. [Google Scholar]
- Norman, D.A. The Design of Everyday Things; Basic Books: New York, NY, USA, 1988. [Google Scholar]
- Conole, G.; Dyke, M. Understanding and using technological affordances: A response to Boyle and Cook. Res. Learn. Technol. 2004, 12, 301–308. [Google Scholar] [CrossRef]
- Oliver, M. Learning technology: Theorising the tools we study. Br. J. Educ. Technol. 2013, 44, 31–43. [Google Scholar] [CrossRef]
- Ball, L.; Drijvers, P.; Ladel, S.; Siller, H.-S.; Tabach, M.; Vale, C. (Eds.) Uses of Technology in Primary and Secondary Mathematics Education; Springer: Cham, Switzerland, 2018. [Google Scholar] [CrossRef]
- Borwein, J.M. The experimental mathematician: The pleasure of discovery and the role of proof. Int. J. Comput. Math. Learn. 2005, 10, 75–108. [Google Scholar] [CrossRef]
- Drijvers, P.; Ball, L.; Barzel, B.; Heid, M.K.; Cao, Y.; Maschietto, M. Uses of Technology in Lower Secondary Mathematics Education; Springer: Cham, Switzerland, 2016. [Google Scholar] [CrossRef]
- Oates, G. Integrated Technology in Undergraduate Mathematics: Issues of Assessment. Electron. J. Math. Technol. 2010, 4, 162–174. [Google Scholar]
- Artigue, M. Learning mathematics in a CAS environment: The genesis of a reflection about instrumentation and the dialectics between technical and conceptual work. Int. J. Comput. Math. Learn. 2002, 7, 245–274. [Google Scholar] [CrossRef]
- Loch, B.; Jordan, C.R.; Lowe, T.W.; Mestel, B.D. Do screencasts help to revise prerequisite mathematics? An investigation of student performance and perception. Int. J. Math. Educ. Sci. Technol. 2014, 45, 256–268. [Google Scholar] [CrossRef]
- Rakes, C.R.; Valentine, J.C.; Mcgatha, M.B.; Ronau, R.N. Methods of Instructional Improvement in Algebra: A Systematic Review and Meta-Analysis. Rev. Educ. Res. 2010, 80, 372–400. [Google Scholar] [CrossRef]
- Takači, D.; Stankov, G.; Milanovic, I. Efficiency of learning environment using GeoGebra when calculus contents are learned in collaborative groups. Comput. Educ. 2015, 82, 421–431. [Google Scholar] [CrossRef]
- Jaworski, B.; Matthews, J. Developing teaching of mathematics to first year engineering students. Teach. Math. Applic. 2011, 30, 178–185. [Google Scholar] [CrossRef]
- Howard, E.; Meehan, M.; Parnell, A. Live lectures or online videos: Students’ resource choices in a first-year university mathematics module. Int. J. Math. Educ. Sci. Technol. 2018, 49, 530–553. [Google Scholar] [CrossRef]
- McKnight, C.; Magid, A.; Murphy, T.J.; McKnight, M. Mathematics Education Research: A Guide for the Research Mathematician; American Mathematical Society: Providence, RI, USA, 2000. [Google Scholar]
- King, S.O.; Robinson, C.L. ‘Pretty Lights’ and Maths! Increasing student engagement and enhancing learning through the use of electronic voting systems. Comput. Educ. 2009, 53, 189–199. [Google Scholar] [CrossRef]
- Thiel, T.; Peterman, S.; Brown, M. Addressing the Crisis in College Mathematics: Designing Courses for Student Succes. Change Mag. High. Learn. 2008, 40, 44–49. [Google Scholar] [CrossRef]
- Brown, B.; Jacobsen, M.; Lambert, D. Learning technologies in higher education. In Proceedings of the IDEAS: Rising to Challenge Conference, University of Calgary, Calgary, AB, Canada, 9–10 May 2014; pp. 25–43. [Google Scholar]
- Lai, J.; Bower, M. How is the use of technology in education evaluated? A systematic review. Comput. Educ. 2019, 133, 27–42. [Google Scholar] [CrossRef]
- Ruben, R. Puentedura’s Blog: Transformation, Technology, and Education. 2006. Available online: http://hippasus.com/resources/tte/ (accessed on 15 November 2022).
- FaSMEd: FaSMEd Framework. 2020. Available online: https://microsites.ncl.ac.uk/fasmedtoolkit/theory-for-fa/the-fasmed-framework/ (accessed on 15 November 2022).
- Buchanan, T.; Sainter, P.; Saunders, G. Factors affecting faculty use of learning technologies: Implications for models of technology adoption. J. Comput. High. Educ. 2013, 25, 1–11. [Google Scholar] [CrossRef]
- Nikou, S.A.; Economides, A.A. Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Comput. Educ. 2017, 109, 56–73. [Google Scholar] [CrossRef]
- Zogheib, B.; Rabaa’i, A.; Zogheib, S.; Elsaheli, A. University student perceptions of technology use in mathematics learning. J. Inf. Tech. Educ. Res. 2015, 14, 417–438. [Google Scholar] [CrossRef] [PubMed]
- Mishra, P.; Koehler, M.J. Technological pedagogical content knowledge: A framework for teacher knowledge. Teach. Coll. Rec. 2006, 108, 1017–1054. [Google Scholar] [CrossRef]
- 3E Education: 3E Framework. Available online: https://3eeducation.org/3e-framework/ (accessed on 15 November 2022).
- Aparicio, M.; Bacao, F.; Oliveira, T. An e-Learning Theoretical Framework. Educ. Technol. Soc. 2016, 19, 292–307. [Google Scholar]
- Laurillard, D. Rethinking University Teaching: A Conversational Framework for the Effective Use of Learning Technologies, 2nd ed.; Routledge: London, UK, 2013. [Google Scholar]
- Venkatesh, V.; Thong, J.Y.L.; Xu, X. Unified theory of acceptance and use of technology: A synthesis and the road ahead. J. Assoc. Inf. Syst. 2016, 17, 328–376. [Google Scholar] [CrossRef]
- Kieran, C.; Drijvers, P. Digital Technology and Mathematics Education: Core Ideas and Key Dimensions of Michèle Artigue’s Theoretical Work on Digital Tools and Its Impact on Mathematics Education Research. In The Didactics of Mathematics: Approaches and Issues; Hodgson, B.R., Kuzniak, A., Lagrange, J.-B., Eds.; Springer: Cham, Switzerland, 2016; pp. 123–142. [Google Scholar] [CrossRef]
- Lopes, J.B.; Costa, C. Digital Resources in Science, Mathematics and Technology Teaching—How to convert Them into Tools to Learn. In Technology and Innovation in Learning, Teaching and Education. TECH-EDU 2018. Communications in Computer and Information Science; Tsitouridou, M., Diniz, J.A., Mikropoulos, T., Eds.; Springer Nature: Cham, Switzerland, 2019; Volume 993, pp. 243–255. [Google Scholar] [CrossRef]
- National Research Coucil. Adding it Up: Helping Children Learn Mathematics; Kilpatrick, J., Swafford, J., Findell, B., Eds.; The National Academies Press: Washington DC, USA, 2001. [Google Scholar] [CrossRef]
- Handal, B.; El-Khoury, J.; Campbell, C.; Cavanagh, M. A framework for categorising mobile applications in mathematics education. In Proceedings of the Australian Conference on Science and Mathematics Education, Australian National University, Canberra, Australia, 19–21 September 2013; pp. 142–147. [Google Scholar]
- Bower, M. Deriving a typology of Web 2.0 learning technologies. Br. J. Educ. Technol. 2016, 47, 763–777. [Google Scholar] [CrossRef]
- Abderraim, E.M.; Mohamed, E.; Azeddine, N. An evaluation model of digital educational resources. Int. J. Emerg. Technol. Learn. 2013, 8, 29–35. [Google Scholar] [CrossRef]
- Goodwin, K. Use of Tablet Technology in the Classroom. In New South Wales Curriculum and Learning Innovation Centre Report. 2012. Available online: https://cpb-ap-se2.wpmucdn.com/global2.vic.edu.au/dist/1/42368/files/2014/04/iPad_Evaluation_Sydney_Region_exec_sum-1pjdj70.pdf (accessed on 15 November 2022).
- Pechenkina, E. Developing a typology of mobile apps in higher education: A national case-study. Australas. J. Educ. Technol. 2017, 33, 134–146. [Google Scholar] [CrossRef]
- Hoyles, C.; Noss, R. The technological mediation of mathematics and its learning. Hum. Dev. 2009, 52, 129–147. [Google Scholar] [CrossRef]
- Intertwingled: Peter Morville’s User Experience Honeycomb. 2016. Available online: https://intertwingled.org/user-experience-honeycomb/ (accessed on 15 November 2022).
- CAST: The UDL Guidelines. 2018. Available online: http://udlguidelines.cast.org/ (accessed on 15 November 2022).
- Baldwin, S.J.; Ching, Y.H. An online course design checklist: Development and users’ perceptions. J. Comput. High. Educ. 2019, 31, 156–172. [Google Scholar] [CrossRef]
- Atkinson, S. Embodied and Embedded Theory in Practice: The Student-Owned Learning-Engagement (SOLE) Model. Int. Rev. Res. Open Distrib. Learn. 2011, 12, 1–18. [Google Scholar] [CrossRef]
- Kirkpatrick, D.; Kirkpatrick, J. Evaluating Training Programs: The Four Levels, 3rd ed.; Berrett-Koehler Publishers: Oakland, CA, USA, 2006. [Google Scholar]
- Pickering, J.D.; Joynes, V.C.T. A holistic model for evaluating the impact of individual technology-enhanced learning resources. Med. Teach. 2016, 38, 1242–1247. [Google Scholar] [CrossRef]
- Rodríguez, P.; Nussbaum, M.; Dombrovskaia, L. Evolutionary development: A model for the design, implementation, and evaluation of ICT for education programmes. J. Comput. Assist. Learn. 2012, 28, 81–98. [Google Scholar] [CrossRef]
- Gueudet, G.; Pepin, B. Didactic Contract at the Beginning of University: A Focus on Resources and their Use. Int. J. Res. Undergrad. Math. Educ. 2018, 4, 56–73. [Google Scholar] [CrossRef]
- Wiliam, D.; Thompson, M. Integrating Assessment with Learning: What Will It Take to Make It Work. In The Future of Assessment: Shaping Teaching and Learning, 1st ed.; Dwyer, C.A., Ed.; Routledge: New York, NY, USA, 2008; pp. 53–82. [Google Scholar] [CrossRef]
- Adnan, N.H.; Ritzhaupt, A. Software Engineering Design Principles Applied to Instructional Design: What can we Learn from our Sister Discipline? TechTrends 2018, 62, 77–94. [Google Scholar] [CrossRef]
- Svihla, V. Design Thinking and Agile Design. In Foundations of Learning and Instructional Design Technology, 1st ed.; West, R.E., Ed.; Pressbooks: Montreal, QC, Canada, 2018; Available online: https://lidtfoundations.pressbooks.com (accessed on 15 November 2022).
- Ruben, R. Puentedura’s Blog: SAMR and TPCK: Intro to Advanced Practice. 2010. Available online: http://hippasus.com/resources/sweden2010/SAMR_TPCK_IntroToAdvancedPractice.pdf (accessed on 15 November 2022).
- Drijvers, P.; Monaghan, J.; Thomas, M.O.J.; Trouche, L. Use of Technology in Secondary Mathematics. In Final Report for the International Baccalaureate. 2014. Available online: https://hal.archives-ouvertes.fr/hal-01546747 (accessed on 15 November 2022).
- Handal, B.; Campbell, C.; Cavanagh, M.; Petocz, P.; Kelly, N. Integrating Technology, Pedagogy and Content in Mathematics Education. J. Comput. Math. Sci. Teachnol. 2012, 31, 387–413. [Google Scholar]
- Hilton, J.T. A Case Study of the Application of SAMR and TPACK for Reflection on Technology Integration into Two Social Studies Classrooms. Soc. Stud. 2016, 107, 68–73. [Google Scholar] [CrossRef]
- Kimmons, R.; Hall, C. How Useful are our Models? Pre-Service and Practicing Teacher Evaluations of Technology Integration Models. TechTrends 2018, 62, 29–36. [Google Scholar] [CrossRef]
- Reeves, T.C.; Benson, L.; Elliott, D.; Grant, M.; Holschuh, D.; Kim, B.; Kim, H.; Lauber, E.; Loh, S. Usability and Instructional Design Heuristics for E-Learning Evaluation. In Proceedings of the ED-MEDIA 2002 World Conference on Educational Multimedia, Hypermedia & Telecommunications, Denver, CO, USA, 24–29 June 2002. [Google Scholar]
- Squires, D.; Preece, J. Predicting quality in educational software: Evaluating for learning, usability and the synergy between them. Interact. Comput. 1999, 11, 467–483. [Google Scholar] [CrossRef]
- Slade, C.; Downer, T. Students’ conceptual understanding and attitudes towards technology and user experience before and after use of an ePortfolio. J. Comput. High. Educ. 2020, 32, 529–552. [Google Scholar] [CrossRef]
- Molich, R.; Nielsen, J. Improving a human-computer dialogue. Commun. ACM 1990, 33, 338–348. [Google Scholar] [CrossRef]
- NN/g Nielsen Norman Group: Jakob Nielsen’s 10 Heuristics for User Interface Design. 2020. Available online: http://www.nngroup.com/articles/ten-usability-heuristics/ (accessed on 15 November 2022).
- JISC Guide: Usability and User Experience. 2014. Available online: https://www.jisc.ac.uk/guides/usability-and-user-experience (accessed on 15 November 2022).
- Meyer, A.; Rose, D.H.; Gordon, D. Universal Design for Learning: Theory and Practice; CAST Professional Publishing: Wakefield, MA, USA, 2014. [Google Scholar]
- Rose, D.H.; Meyer, A. Teaching Every Student in the Digital Age: Universal Design for Learning; Association for Supervision and Curriculum Development (ASCD): Alexandria, VA, USA, 2002. [Google Scholar]
- Kumar, K.L.; Wideman, M. Accessible by design: Applying UDL principles in a first year undergraduate course. Can. J. High. Educ. 2014, 44, 125–147. [Google Scholar] [CrossRef]
- Drijvers, P.; Tacoma, S.; Besamusca, A.; Doorman, M.; Boon, P. Digital resources inviting changes in mid-adopting teachers’ practices and orchestrations. ZDM—Math. Educ. 2013, 45, 987–1001. [Google Scholar] [CrossRef]
Literature to Include | Literature to Exclude | Databases to Include |
---|---|---|
2001 onwards, Peer reviewed, Higher/post-primary education, Published in English, Full text available in library or online | Reports, Grey literature, Primary-school education | Education Research Complete, British Education Index, ERIC and Academic Search Complete (all available via EBSCO), Web of Science, Scopus |
Research Area | Search Terms | Number of Articles after Final Scan |
---|---|---|
RA1 | ‘student engagement’, ‘technology’, ‘technology use’, ‘digital tools’, ‘higher education’, ‘undergraduate education’, ‘mathematics’. | 45 |
RA2 | ‘mathematics educational technology’ or ‘mathematics technology tools’, ‘evaluations’, and ‘investigations’, and ‘undergraduate’ or ‘higher education’. | 61 |
RA3 | RA2 search terms plus ‘frameworks’, ‘models’, ‘categorisations’, ‘characterisations’, ‘typologies’, and ‘classifications’. | 88 |
Duplicated papers | 40 | |
Seminal added (prior to year range 2000–2020) | 6 |
Study | Engagement Dimension and Indicator Measured | Pedagogical Use of Technology | Factor and/or Impact |
---|---|---|---|
Trenholm et al. [51] | Cognitive engagement: Scale to measure approach to learning (R-SPQ-2F) | Optional use of live versus recorded lectures. | Students used videos because of self-paced nature of their availability. Students with high use of videos more inclined to take surface approach to learning than others. |
Steen-Utheim and Foldnes [50] | Affective Engagement: Kahu’s model of student engagement [8] | Flipped classroom approach in 1st year undergraduate mathematics course. | Peer and lecturer relationships, and possibly class size, influenced positive engagement outcome. |
Kanwal [57] | Behaviour engagement: Activity Theory | Automated system to support solving of mathematical tasks, variety of technology resources including GeoGebra, MyMathlab, YouTube, and online calculators. | Exam preparation encouraged engagement. Using powerful automated calculators diverted students from engagement with required mathematical operations. |
Thomas et al. [55] | Cognitive Engagement: Instrumental orchestration | Variety of innovative technologies and tasks including Desmos, GeoGebra, KakooTalk. | Engagement ensured through sustained intensive use of technologies; teacher privileging of technology; ease of use; ability to visualise mathematics; and integration in assessment. |
Anastasakis et al. [69] | Behaviour engagement: Activity Theory | Self-selected resources (both digital and non-digital) 2nd year engineering mathematics. | High mark in exams was student goal for selecting and engaging in resource. |
Category | Benefits | Studies | Technology Used | Context |
---|---|---|---|---|
Pragmatic | Calculations and graphing | Jarvis et al. [78] | Sage | HE M |
Varavsky (as cited in [14]) | Computer Algebra System (CAS) | 1Y UM | ||
Thomas et al. [52] | Multiple technologies | 1Y UM | ||
Epistemic | Problem Solving | Loch et al. [114] | Screencast | 1Y UM |
Takači et al. [116] | Computer supported collaborative learning (CSCL) | 1Y UM | ||
Mathematical Understanding | Galligan et al. [53] | Tablets | 1Y UM | |
Takači et al. [116] | CSCL | 1Y UM | ||
Triantafyllou et al. [101] | Multiple technologies | 1Y UM | ||
Aventi (as cited in [14]) | GeoGebra | Year 9 maths (Australasia) | ||
Thomas et al. [52] | Multiple technologies | 1Y UM | ||
Buteau et al. [71] | CAS | HE M | ||
Rote Learning (negative) | Trenholm et al. [104] | e-lectures | HE M | |
Visualisation | Jarvis et al. [78] | Sage | HE M | |
Lavicza [81] | CAS | HE M | ||
Takači et al. [116] | GeoGebra | 1Y UM | ||
Jaworski and Matthews [117] | GeoGebra | 1Y UM | ||
Thomas et al. [52] | Multiple technologies | 1Y UM | ||
Feedback | Trenholm et al. [93] | Fully Asynchronous Online (FAO) | HE M | |
King and Robinson [102] | Audience Response Systems (ARS) | HE M | ||
Lee [103] | Online quizzes | HE M | ||
Real World Problems | Jarvis et al. [78] | Sage | HE M | |
Lavicza [81] | CAS | HE M | ||
Conceptual and Procedural Understanding | Rakes et al. [115] | Various strategies that included technology | Mathematics Education | |
Other | Engagement (motivation) | Loch et al. [114] | Screencasts | 1Y UM |
Galligan et al. [53] | Tablets | 1Y UM | ||
King and Robinson [102] | ARS | 2Y EM | ||
Thomas et al. [52] | Multiple technologies | 1Y UM | ||
Buteau et al. [71] | CAS technologies | HE M | ||
Self-regulated learning, self-paced, and self-directed learning | Loch et al. [114] | Screencast | 1Y UM | |
Trenholm et al. [104] | Recorded Video lectures | HE M | ||
Jarvis et al. [78] | Sage | HE M | ||
Triantafyllou et al. [101] | Khan Academy and other online resources | 1Y UM | ||
Buteau et al. [71] | CAS | HE M | ||
Howard et al. [118] | Recorded Video lectures | 1Y UM | ||
Kanwal [54] | Online learning environment | 1Y UM | ||
Satisfaction | Trenholm et al. [104] | Recorded Video lectures | HE M | |
King and Robinson [102] | ARS | 2Y EM | ||
Triantafyllou et al. [101] | Khan Academy and other online resources | 1Y UM | ||
Lee [103] | Online learning technologies | Graduate students | ||
Classroom Management | King and Robinson [102] | ARS | 2Y EM | |
Assessment | Oates [112] | CAS | HE M | |
Approaches to learning | Trenholm et al. [48] | Recorded video lectures | 1Y UM | |
Howard et al. [118] | Recorded video lectures | 1Y UM |
Measure | Study |
---|---|
Student and/or teacher views of resources through use of surveys, scales, or questionnaires | Jaworski and Matthews [118], King and Robinson [121], Lee [104], Lavicza [28], Loch et al. [115], Oates [113], Thiel et al. [122], Thomas et al. [55], Trenholm et al. [51,94], Triantafyllou et al. [102], Howard et al. [119]. |
Test, exam, or quiz results for improved students’ mathematical understanding | Jaworski and Matthews [118], King and Robinson [121], Loch et al. [100], Takači et al. [117], Howard et al. [119]. |
Recorded usage of resources | Loch et al. [100], Trenholm et al. [51], Howard et al. [119]. |
Attendance data | King and Robinson [121], Howard et al. [119] |
Course artefacts and/or curriculum materials | Jarvis et al. [80], Lavicza [28], Thomas et al. [55] |
Student and/or teacher interviews | Jarvis et al. [80], Jaworski and Matthews [118], King and Robinson [121], Lavicza [28] |
Teacher practices, reflections, and/or blogs | Galligan et al. [56], Jaworski and Matthews [118], King and Robinson [121]. |
Class observations | Jaworski and Matthews [118], King and Robinson [121], Lavicza [28], Thomas et al. [55]. |
Task analysis | Takači et al. [117], Thomas et al. [55]. |
Scale to measure approach to learning (scale used is R-SPQ-2F) | Trenholm et al. [51,94]. |
Case Study | Drijvers [11]. |
Theory | Study |
---|---|
Community of inquiry (CoI) and documental genesis | Jaworski and Matthews [118] |
Computer-supported collaborative learning (CSCL) | Takači et al. [117] |
Laurillard conversational framework | King and Robinson [103] |
Conceptual model of affective and cognitive effects of human and design factors | Piccoli et al. (as cited in Lee [104]) |
Instrumental orchestration | Thomas et al. [55] |
Taxonomy for integrated technology (author’s own version from Ph.D. thesis) | Oates [113] |
Group | Framework | Description/Purpose | Study or Website |
---|---|---|---|
Technology integration | Substitution Augmentation Modification and Redefinition (SAMR) | Model describes 4 levels of technology integration in tasks | http://hippasus.com/resources/tte/ Puentedura [125] |
Formative Assessment in Science and Mathematics Education (FaSMEd) * | Characterisation of aspects of classroom integration of formative assessment technology tools | https://microsites.ncl.ac.uk/fasmedtoolkit/theory-for-fa/the-fasmed-framework/ FaSMEd [126] | |
Technology Acceptance Model (TAM) | Theorises usage behaviour of technology | https://en.wikipedia.org/wiki/Technology_acceptance_model Buchanan et al. [127] Nikou and Economides [128] Zogheib et al. [129] | |
Technological pedagogical content knowledge (TPACK) *** | Framework considers intersection of teachers’ knowledge on technology, pedagogy, and content key to successful technology integration. | Mishra and Koehler [130] | |
Classification system * (Bray and Tangney **) [74] | Classification system with 4 components: Technology, Learning Theory, SAMR level, Purpose. | Bray and Tangney [74] | |
3E (Enhance, Extend, Empower) Framework | Guidance and examples to exploit technology to enhance, extend, empower teaching and learning. | https://3eeducation.org/3e-framework/ [131] | |
eLearning theoretical framework | eLearning systems theory framework that draws out roles of people, technology, and services in learning provision, | Aparicio et al. [132] | |
Laurillard Conversational Framework | Framework describes interactions and types of activities that occur between teachers and students for effective learning. | King and Robinson [103] Laurillard [133] | |
Unified theory of acceptance and use of technology (UTUAT) | Alternative to TAM—4 key factors in accepting technology: performance expectancy, effort expectancy, social influence, facilitating conditions. | Venkatesh et al. [134] | |
4C (Connection, Communication, Collaboration, Creating) Framework | Framework to organise technology use in higher education. | Brown et al. [123] | |
Theoretical Frameworks | Instrumental Orchestration * | Converting digital tools into artefacts, connecting technical skills and conceptual understanding required. | Artigue [114] Kieran and Drijvers [135] Lopes and Costa [136] Thomas et al. [55] |
Didactic Tetrahedron * | Examining digital tool use as interactions between (1) tools and knowledge, (2) tools, knowledge and learner, and integration of (3) tools in curriculum or classroom. | Trgalová et al. [95] | |
Mathematical Proficiency * | Five strands of mathematical proficiency required to learn maths successfully. | National Research Council [137] | |
Pedagogical Opportunities * | Ten pedagogical opportunities grouped into 3 levels: task that has been set, classroom interaction, maths topic. | Pierce and Stacey [15] | |
Didactical Functions * | Three didactical functions supported by technology: (1) Do, (2) Learn–Practice Skills, and (3) Learn-concepts. | Drijvers [11] | |
Technology Affordances and Types | Mobile App Categorisation * (Handal **) | Categorises use of mobile apps for schools based on instructional roles and media richness as: Productive, Explorative and Instructive. Uses Goodwin’s classification—see below. | Handal et al. [138] |
Web 2 typology (Bower **) | Typology of web 2 tools suitable for teaching and learning; includes what they have been used for, pedagogical uses and examples. | Bower [139] (p. 772) | |
Evaluation Grid for multimedia tools (Abderrahim, Mohamed and Azeddine **) | Checklist to ascertain quality of multimedia tools: pedagogical, didactical, and technical. Derived from tools used in secondary education in Morocco. | Abderrahim et al. [140] | |
Classification of Mobile Apps (Goodwin **) | Precursor to Handal’s categorisation concerned with users’ level of control over tasks and activities, for school-based apps: Instructive, Manipulative, and Constructive. | Goodwin [141] (p. 26) | |
Typology of mobile apps (Pechenkina **) | Typology of mobile apps used in higher education institutions in Australia by order of most used types: Organiser, Navigator, and Instructive. | Pechenkina [142] (pp. 139–140) | |
Categories of digital tools * (Hoyles and Noss **) | Four categories of tools: (1) dynamic and graphical tools, (2) tools that outsource processing power, (3) new representational infrastructures, and (4) implications of high-bandwidth connectivity on nature of maths activity. | Hoyles and Noss [143] | |
Experimental mathematician * (Borwein **) | Use or affordances of a computer in mathematics, focusing on proofs. | Borwein [111] | |
User Experience | User Experience Honeycomb | Seven attributes of technology deemed desirable to enhance student experience of using technology. | Morville [144] |
Universal Design for Learning (UDL) | Framework used to provide fully inclusive learning environment for all students. Three main elements: Engagement, Representation, and Action and Expression, considering multiple means to achieve these. | Center for Applied Special Technology (CAST) [145] | |
Online Course Design Learning Checklist (OCDLC) | Before, during, and after checklist, with 3, 6, and 10 items, respectively, for online courses in higher education. | Baldwin and Ching [146] | |
Student-Owned Learning-Engagement (SOLE) model | Theoretical Framework on eLearning systems with 3 dimensions: users, technology, and services. | Atkinson [147] | |
FEM Framework for Engagement in Mathematics (FEM) * | Three aspects: Pedagogical Relationships (between students and teachers), Pedagogical Repertoires (teacher day-to-day teaching practices), and Student Engagement (factors supporting engagement). | Attard and Holmes [67] |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ní Shé, C.; Ní Fhloinn, E.; Mac an Bhaird, C. Student Engagement with Technology-Enhanced Resources in Mathematics in Higher Education: A Review. Mathematics 2023, 11, 787. https://doi.org/10.3390/math11030787
Ní Shé C, Ní Fhloinn E, Mac an Bhaird C. Student Engagement with Technology-Enhanced Resources in Mathematics in Higher Education: A Review. Mathematics. 2023; 11(3):787. https://doi.org/10.3390/math11030787
Chicago/Turabian StyleNí Shé, Caitríona, Eabhnat Ní Fhloinn, and Ciarán Mac an Bhaird. 2023. "Student Engagement with Technology-Enhanced Resources in Mathematics in Higher Education: A Review" Mathematics 11, no. 3: 787. https://doi.org/10.3390/math11030787
APA StyleNí Shé, C., Ní Fhloinn, E., & Mac an Bhaird, C. (2023). Student Engagement with Technology-Enhanced Resources in Mathematics in Higher Education: A Review. Mathematics, 11(3), 787. https://doi.org/10.3390/math11030787