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There is so much educational, learning and EdTech research out there it can be difficult to keep up. This overwhelm, unfortunately, leads to a situation where many intriguing outcomes do not receive the attention (or scrutiny) they deserve towards improving the education sector.

In this first delivery, we’ve gathered some of the hottest ideas that EdTech instructors, designers, administrators and developers might find worth trying in their everyday practice. The following is a list of reviews, which means these articles gather and analyze existing research rather than produce their own raw results.

If you have ideas, questions, suggestions or stories, we would love to know them! Please leave us a comment below.

Try this: adapt and combine tech-adapted methodologies in your mathematics teaching

Lishon-Savarino, 2016. Systematic Review of Online Developmental Mathematics Adaptive Learning Technology Intervention Investigation. Nova Southeastern University Dissertation (Paywalled).

This research looks to find out how adaptive learning technologies have been implemented into post-secondary mathematics. While only an exploratory research, it suggests a strong correlation between an in-depth strategy and design phase, with outcomes by implementation of adaptive technology. Combinations of methodologies seem to be promising and will be the subject of further research.

Try this: evaluate Moodle from a stakeholder engagement standpoint

Heathcote and Palmer, 2016. Designing a Review of the Learning Management SystemProceedings from ASCILITE Adelaide 2016 (PDF).

To complement traditional “functional” evaluations of an LMS, this research broadens the set of goals attained to an LMS implementation in a university context. When users gain some experience of EdTech for lifelong learning, their expectations about an LMS change. Since this fact is not often recognized, these expectations tend to stay unmet. This research introduces a “stakeholder engagement” level ―with a Use Cases component― to an LMS procurement evaluation, which, they argue, provides a longer term view focused on strategic value rather than standard matrix functionality scoring.

Try this: update your learning IT management priorities

Toperesu and Van Belle, 2016. Mobile Learning Management Issues in Higher Education: A Retrospective and Prospective Review. Proceedings of the 5th International Conference on M4D Mobile Communication Technology for Development, (PDF, page 51).

What are the IT management issues arising from the increase of mobile learning, and its corresponding pedagogical shifts, in the developing world’s classrooms? These South Africa-based research tracks concerns and strategies taken up by IT administrators in the past three years. Security and privacy have jumped to the forefront of concerns, while the opposite is true for “Student Success Technologies”. It proposes a role for IT staff as “EdTech optimizers”.

Try this: be mindful of your students’ personality in the design and management of your course

Khatibi and Khormaei, 2016. Learning and Personality: A Review. Journal of Educational and Management Studies, Vol. 6, No. 4 (PDF).

By including the element of personality in the study of learning processes, the researchers take another, critical, look at learning styles, which in recent years have been doubted and even deemed as “myth”. Personality, they argue, could better articulate personal psychology traits that set the basis for learning, such as memory, decision-making and motivation. If personality as a factor holds water, the implications in design for academic achievement, and the potential “psychometric problems,” could be a game changer.

Try this, but for the right reasons: the cloud

Kayali, Safie and Mukhtar, 2016. Literature Review of Cloud Based E-learning Adoption by Students: State of the Art and Direction for Future Work. IRIS IOP Conf. Series: Material Science and Engineering, No. 160 (PDF).

This meta-analysis takes a look at how the rationales for adopting cloud-based learning solutions have evolved. Models with names like “Technology Acceptance Model”, “Technology-Organization Environment” or “Diffusion of Innovation” are placed on a chart of factors ranging from economics and quality of service, to social influence and expectations, to virtual environments as a learning industry prerogative. Consumer preferences and social pressures dominate the cloud-based learning EdTech procurement process, something that gives some learning advocates a cause for concern.

Try this: involve your students’ accelerometers in your teaching

Trujillo and González, 2016. Uses of accelerometer sensor and its application in m-learning environments: a review of literature. Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality (Paywalled).

For at least the past 6 years, there has been a vivid interest on the use of sensors, particularly on mobile devices, to increase interactivity and engagement. Accelerometers, or the sensors that measure and capture tridimensional movement and acceleration, have been used twofold: to capture data, from user actions or the device itself; and to respond to the user actions to reinforce the learning process, often in augmented reality or “serious games” activities.

Try this: support more NEET re-engagement intervention research

Mawn, Oliver et al., 2017. Are we failing young people not in employment, education or training (NEETs)? A systematic review and meta-analysis of re-engagement interventions. Systematic Reviews, Vol. 6, No. 16.

Vocational training and friends are often called to the rescue of the unmotivated youth, estimated at 40% worldwide, and steadily critical across regions and income brackets. This British research applies “randomised and quasi-randomized trials with a concurrent or counterfactual control group” to assess the effectiveness of educational, vocational, counseling or service-based programs. While the desired outcome of this analysis is to develop cost-effective social welfare interventions, results from existing studies are too limited and inconsistent to support new policy. Besides positive correlations between”high intensity multi-component interventions” and employment (not really significant results for earnings), the real value of the research seems to be to highlight a need for quality research with better “methodological rigour and reporting”.


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