Learning Analytics, Educational Data Mining, Adaptive Learning

Content mining of archival materials can make for amazing discoveries. Here's how to prepare for the coming influx of researchers who will want access to digital archives as a data source.

Universities’ growing addiction to tracking progress will destroy the very things we are supposed to nurture

Data generated from activities both inside and outside the classroom can be instrumental in understanding student success.

The Predictive Analytics Reporting (PAR) Framework was launched in 2011. PAR's Ellen Wagner discusses insights from four years of exploring the impact of predictive modeling for improving postsecondary student success.

Can we imagienPersonal data collection has long been used to boost productivity but could tiny microphones – embedded in each employee’s own lanyard – be about to change the face of office culture forever?

A Deloitte team in Newfoundland adopted the pilot project last winter during office renovations – CBC News recently reported on its impact. According to one in-house HR expert, it’s been a huge success.

"The minute that you get the report that you're not speaking enough and that you don't show leadership, immediately, the next day, you change your behaviour," Silvia Gonzalez-Zamora told CBC News.

"It's powerful to see how people want to display better behaviours or the behaviours that you're moving them towards,” added the analytics leader.

The concept isn’t as Orwellian as you might think – while the microphones pick up tone of voice and frequency of contributions during meetings, they don’t record specific conversations.

Similarly, accelerometers measure body language and track how often an employee pushes away from their desk – but don’t count coffee breaks or trips to the toilet.

All the data collected is done so anonymously and each employee is assigned their own confidential ID – this way they can compare their own behaviour against that of other participants without fear of reprisal.

Institutional readiness for learning analytics. Is sounds like a dream. And it is a dream.  , it was the title for a conference LACE project organised in collaboration with University of Amsterdam middle of December. Through exploring  a number of pilots organised at UvA, a detour to the swamps of interoperability and standardisation, an introduction to the practice of institutional readiness consultations, the around 40 participants gathered in Allard Pierson Museum in Amsterdam were eventually invited to develop visions of the future. Judging from the evaluations sheets filled out in the end the experience had been ‘educational’ with enough slides, receiving more than ‘good’ marks, both in content and organisation.

According to ResearchGate, the academic social networking site, their RG Score is “a new way to measure your scientific reputation”. With such high aims, Peter Kraker, Katy Jordan and Elisabeth Lex take a closer look at the opaque metric. By reverse engineering the score, they find that a significant weight is linked to ‘impact points’ – a similar metric to the widely discredited journal impact factor.Transparency in metrics is the only way scholarly measures can be put into context and the only way biases – which are inherent in all socially created metrics – can be uncovered.

This fall, Oral Roberts University (OK) issued Fitbits to on-campus students and Garmin vivofits to online students — part of the "whole person" philosophy at the Tulsa-based institution that urges students to be "well prepared" physically. The data generated by those activity trackers on movement, heart rate and sleep patterns drizzles automatically into the university's D2L gradebook in time for settling up midterm grades and finals. The results are displayed through D2L for faculty and students, just as if they were weekly quiz grades. The Garmin device, added CIO Mike Mathews, syncs with an online service that allows students to set goals and share progress with others.

Eventually, the campus will use the analytics to find out whether tracking the fitness data and making it visible gets students to move their bodies more, which is the goal, after all.

Nearly four out of five college students in a recent survey said that having immediate access to data analytics regarding their academic performance had a positive impact on their learning experience. The study, conducted by Hanover Research on behalf of McGraw-Hill Education, suggested that students seek the same kind of immediate feedback in the classroom as they get from social media.

The survey of 2,657 college students found that almost two-thirds of students believe the impact of analytics reports on their academic performance is "very positive." Three-quarters of the students said adaptive learning is "very helpful" to them in retaining new concepts. Adaptive learning technology is designed to personalize students' learning experiences based on their command of course material, enabling them to focus their attention on the concepts they need help understanding, at the moment they need it.

Introduction

There’s something big happening in the world of technology.  Over the past couple of years there’s been a resurgent interest in neural networks and excitement over the challenging problems that they can now solve.  Folks are talking about Deep Learning…  I’ve been keeping an eye on what’s happening in the field to see if there’s anything that we can use to build better tools for researchers here at Mendeley.  Recently I went along to the Re-Work’s Deep Learning Summit and thought I’d share my experiences of it here.

This literature review, list of definitions, and resources provide a guide for community college leaders evaluating analytics for their institutional technology to promote student success. In the end, a technology strategy inclusive of analytics and combined with an unwavering focus on student achievement might prove an essential precursor to student success at all colleges.

Welcome to our project Transforming Learning and Teaching with Practical Analytics.

Learning analytics take advantage of large data sets that relate to student online behaviour. These data sets are analysed to inform approaches that help staff make meaningful and informed decisions around student learning and retention, as well as strengthen student retention and success.

There are systems, such as learning analytics, for staff to understand and interpret student behaviour in Blackboard but what is required is understanding and training in the use of analytics and predictive analytics to make better use of these tools.

The project will develop a practical approach to learning analytics (what we term practical analytics) by providing feedback to academic and teaching staff to support meaningful blended delivery. The project will enable learning analytics for early intervention and support academic staff to translate data into improvement in their teaching practice. We aim to increase the number of staff capable of easily accessing and applying analytics to their teaching practice.