Over the past few months, CLT have been looking into some of the key technological trends set to influence the higher education sector in the next few years. We looked at the benefits they may provide to teaching and learning at LSE (and indeed, other institutions), and the considerations that need to be made before these technologies are implemented.
Using horizon scanning techniques to identify suitable reports, academic articles, media articles and blog posts by institutions and commentators working in the field, four key technological trends were identified through this method; Massive Open Online Courses (MOOCs), Bring Your Own Devices (BYOD), Gamification and Games-based learning and Learning Analytics.
A report on our research, Trends in Educational Technology, is now available on LSE Research Online. The report argues that these technologies can be beneficial, and should be embraced if they address institutional needs. However pedagogy must be at the heart of any technological adoption.
The summarized findings of this report are as follows:
MOOCs are unlikely to be the disruptive force that they were initially hyped to be. Despite increases in tuition fees and the option of receiving free, online education via MOOCs, students are still attracted by the opportunities to gain qualifications, experiences and lifelong connections that one gets by taking traditional, taught courses at a University, and employers are as yet hesitant to accept graduates with qualifications gained solely through online courses.
MOOCs could, however, offer flexibility as a tool within existing programmes. They offer reproducibility for courses which remain unchanged year on year, and could be used to promote the quality of teaching and the values of LSE to a wider audience, particularly to prospective postgraduate, international and corporate audiences. For example, they could also be tailored towards trans-national education (TNE) by offering MOOCs in languages and for topics affecting countries with large numbers of potential students, such as India, South Korea, Brazil and the Philippines. MOOCs may even generate revenue through front-end services for students, such as offering credentials, career guidance and tutoring. Tailored online courses could also feature as part of existing corporate programmes, such as MBA programmes, allowing greater flexibility for these students, as well as inculcating vital digital literacy skills.
However, MOOCs require significant investment in time and resources of academics and support staff; institutions typically have to invest between $15,000 and $50,000 in to producing a MOOC (Colman, 2013), including around 100 hours of production time and 8-10 hours a week of academic time for teaching (Kolowich, 2013). Producing a MOOC also does not guarantee that learners will sign up, be fully engaged, or learn anything useful. The majority of students joining MOOCs may be attracted, or indeed constrained, by factors such as curiosity towards the topic, existing knowledge and qualifications, the reputation of the institute and the time they can commit to the course, rather than an implicit desire for recognised qualifications or career motivations.
BYOD and Cloud Computing
Bring Your Own Device (BYOD) and Cloud computing promise lower equipment and software costs, as staff and students are encouraged to bring devices they already use on a day-to-day basis. This could also lead to a subsequent reduction in energy costs from reduction in on-campus equipment, allow students to expand their learning environment, and improve the resilience of teaching at LSE, by allowing students to access course materials and continue learning in challenging times, for example, during bad weather.
However, educational materials would need to be cross-compatible and accessible with both learners’ devices and learning needs, and institutions wishing to promote the idea of students and staff bringing their own devices will need to consider providing appropriate learning spaces which cater for student and staff needs, including easily accessible plug-points to charge their devices, software licenses for device-friendly specialist software, appropriate internet connectivity and security, both in terms of software and physical security. BYOD would also not mean the end of providing equipment to students. Institutions would still have to provide devices for students without the means to provide their own.
Gamification and Games-based learning
Computer games can be considered to be complex learning environments requiring instructional support in cognitive activities, such as decision-making (Wouters & van Oostendorp, 2013). Pivec, (2007) argues that games-based learning could support a constructivist pedagogy, by allowing students to collaborate, interact in virtual environments (in multiplayer games), manage problems and learn through virtual experiences. Gamification could make more routine aspects of learning more interesting, by providing incentives, and a more interesting, user-friendly format.
Institutions considering games-based learning and gamification must take into account that designing games that are accessible to all students, are engaging and lead to positive learner outcomes requires expertise which are often beyond those of the academics interested in using game-based learning, and would probably require external expertise to produce, leading to cost issues (Epper et al., 2012). Institutional infrastructure and equipment needs to be able to handle the requirements of the game or gamified content, and faculty and support staff needs to be able and prepared to produce and maintain games and adapt course content accordingly. Games may also become a distraction for students, or gamification could lead to the opposite outcome of trivialising course aspects, such as attendance.
Learning analysis tools could also provide faster assessment and feedback for students, and be used for evaluating new pedagogical techniques, allowing lecturers, departments and institutions to focus resources more effectively. Learning analytics could be used to improve student retention and support at-risk students by tailoring courses towards the pedagogic needs of students (Johnson et al., 2013).
Learning analytics are an emerging field with few tried and tested analytical methods and tools. Currently, practitioners in this field require specialist expertise and knowledge of the data source and the institutional context it’s situated in to be able to conducted effective analysis. student data may not come in a format which is easily analysed with data from other sources. The granularity of information can also be variable, and therefore data standardisation and pre-processing would have to be carried out to convert data into appropriate formats and granularities for effective analysis (Romero & Ventura, 2013). This could be a time-consuming process at best, and may not be possible in a lot of cases.
It is unclear whether learning analytics can yet provide an accurate measure of students’ learning and engagement, and by focusing on the collection of certain types of data, learning analytics may run the risk of oversimplifying the student experience, while not fully considering the human interactions involved in their learning. If misused, analytics may lead to privacy and ethical issues, such as conflicts with trade unions, disproportionate levels of workload and discrimination of certain students and staff based institutional politics. Misinterpretation or misuse of data could have consequences, not just for students, but also for staff, whose teaching, funding, and employability may be affected.
Colman, D. (2013). The Big Problem for MOOCs Visualized. Open Culture. Retrieved November 12, 2013, from http://www.openculture.com/2013/04/the_big_problem_for_moocs_visualized.html
Epper, R., Derryberry, A., & Jackson, S. (2012). Game-Based Learning: Developing an Institutional Strategy (Research Bulletin). Louisville, Kentucky, USA. Retrieved from http://net.educause.edu/ir/library/pdf/ERB1208.pdf
Kolowich, S. (2013). The Professors Who Make the MOOCs. The Chronicle of Higher Education. Retrieved November 12, 2013, from https://chronicle.com/article/The-Professors-Behind-the-MOOC/137905/#id=overview
Pivec, M. (2007). Editorial: Play and learn: potentials of game-based learning. British Journal of Educational Technology, 38(3), 387–393. doi:10.1111/j.1467-8535.2007.00722.x
Romero, C., & Ventura, S. (2013). Data mining in education. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 3(1), 12–27. doi:10.1002/widm.1075
Wouters, P., & van Oostendorp, H. (2013). A meta-analytic review of the role of instructional support in game-based learning. Computers & Education, 60(1), 412–425. doi:10.1016/j.compedu.2012.07.018