December 12, 2014
USC, IBM, and Fluor Corp to form Center for Applied Innovation in support of Personalized Learning
The University of South Carolina, IBM, and Fluor Corp. are forming the Center for Advanced Innovation to leverage predictive analytic techniques in the development of personalized learning curricula. The center will make use of technology initially developed as a result of IBM’s work with Gwinnet County Public Schools in Georgia.
December 17, 2014
University of Iowa Joins Unizin Consortium
After eliciting broad campus input, the University of Iowa has joined the Unizin Consortium of schools and will participate in a small pilot of Canvas during the summer and fall of 2015.
December 11, 2014
Former School Data Czar Receives Jail Time
Former Columbus City Schools data czar Stephen B. Tankovich has received 15 days of jail time after pleading no contest to attempted tampering with school records. Tankovich denies directing anyone to change student data (specifically attendance records), but rather claims that any changes were the result of acceptable data cleaning practices.
Privacy & Ethics
December 11, 2014
Oregon Attorney General Pushes for Online ‘Bill of Rights’
Oregon Attorney General Ellen Rosenblum is urging state lawmakers to adopt a privacy bill on the model of the one signed by California Governor Jerry Brown in September, requiring school’s contracts with technology vendors to prohibit the collection and dissemination of student information.
December 10, 2014
Completing the Loop: Returning Meaningful Learning Analytic Data to Teachers
The Completing the Loop project was initiated in 2014 with support from the Australian Government, the University of Melbourne, Macquarie University, and the University of South Australia. The stated aim of the project is to “develop a better understanding of learning analytics and the ways in which analytics can be interpreted, applied, and actioned by teachers to improve teaching and learning practices. Phase one of the project has now been complete, with results presented at the 2014 Australian Learning Analytics Summer Institute (November 2014). Preliminary findings from interview data include:
- Participants had fairly basic requests concerning their needs and ideas of how leaning analytics can be used and retrieved from their courses
- Such requests mainly focused on analytics around student engagement, specifically frequency of access to resources
- Due to the blended nature of their teaching, few participants made use of interactive online activities such as quizzes and discussions, limiting the availability of data.
- Only a minority of participants currently monitor their students’ activities using learning analytics.
December 16, 2014
Results of Infamous HILT Attendance Study Released
The Harvard Initiative for Learning and Teaching (HILT) Attendance study, which famously through the university into hot water as a result of privacy concerns, found that courses requiring attendance saw higher attendance rates, and that attendance declined over the course of the semester. Was the study worth it?
December 11, 2014
2014 Educational and Training Content Trends
A recent survey fielded by Data Conversion Laboratory Inc found that 47% of respondents identified a lack of analytics for measuring effectiveness of training as one of the greatest challenge in developing and delivering training content. By far, the most common way of measuring training effectiveness continues to be the use of surveys (59%), with analytics being used by only a quarter of respondents.
December 10, 2014
The Advisory Board Company buys Royall & Company for $850 Million
Since 2012, the Educational Advisory Board has made significant and high-profile moves into the educational analytics space. With the acquisition of Royall, EAB sees a significant increase in its market share in the data-driven student engagement and enrollment solutions space, as well as building out its talent and expertise in support of future projects and initiatives.
A Student App for Learning Analytics by Niall Sclater
Sclater discusses a move on the part of Joint Information Systems Committee (JISC) to commission a range of learning analytics services in support of higher education in the UK. One of the services commissioned as part of this ambitious initiative is an app for students. The requirements gathering process will determine the kinds of features that will have the most value for students, but Sclater here anticipates likely results, important considerations, and possible issues.
Data Science: The New Skillset for Learning Technologists by Mark Aberdour
Aberdour observes the wealth of educational data that is increasingly at our fingertips, and emphasizes the need for increased data literacy…something that is easier to achieve thanks to a growing body of literature and the increased availability of analytical tools. That being said, data science is not something that can just be ‘picked up.’ It requires effort, expertise, and support from local communities of experts. At the end of the day, however, data are only as good as the questions that are asked, and it is in this aspect of data science here that learning technologists are best equipped to start contributing, and can contribute, starting right now.
Big Data: Is Small Beautiful? by Terry Freedman
Freedman presents a cynical view of big data in education and advocates, instead, a view that would see an emphasis on usefulness and relevance over succumbing to big data hype.
Averages Don’t Matter…and Other Common Mistakes in Data Analysis by Nick Sheltrown
Sheltrown offers five important lessons that function as an valuable introduction to methodological issues when working with educational data: “Generally, it is as much work to craft a poor analysis as it is a good one. Adhere to these lessons and you will save countless headaches in drawing value from your data.” Included in his list are (1) the importance of sanity checking, (2) suspicion of averages, (3) caution against using models you don’t understand, (4) acknowledging that actionable analysis requires comparisons, and (5) the fact that working with data is hard to do.
New Report on Emotional Presence in Online Education by Terry Anderson
Anderson summarizes and recommends a new report recently published by the Learning Analytics Community Exchange (LACE), which reviews the literature on emotions and learning, and extends the Community of Inquiry Model to include Emotional Presence. Anderson wonders why the researchers did not include more of an emphasis on teacher emotion, but notes that the piece represents a great starting point for future research.
Murky Federal Privacy Law Puts MOOC Student Data in Questionable Territory by D. Frank Smith
Chief Privacy Officer for the U.S. Department of Education, Kathleen Styles, has said that MOOC data is seldom protected by FERPA. The reason for this is that FERPA only applies to schools receiving funding under an applicable program of the U/S. Department of Education, and MOOCs are rarely funded with Title IV dollars.
Walking the Student Data Tightrope by Dian Schaffhauser
An interview with attorney Bret Cohen, on student privacy issues that should be considered by school districts. The interview highlights the importance of being attuned not simply to legal issues, but political ones as well. When it comes to collecting student data, no notice to parents is technically required, since such data collection is in the service of improving education and student success. However, the success of data collection and analytics initiatives is contingent upon mitigating potential blow-back from parents with an interest in protecting the safety and future prospects of their children. Full transparency and explicit consent for initiatives, may not be legally necessary, but they are nonetheless advisable, if not absolutely necessary.
How the US Government’s Tiny Statistical Error is Distorting the True Cost of College by Zach Wener-Fligner
The US Government places students into income brackets differently than many American colleges, with the result that students in the lowest income bracket appear to be paying more for their education than they actually are.
Assessing the Suitability of Student Interactions from Moodle Data Logs as Predictors of Cross-Curricular Competencies
Santiago Iglesias-Pradas, Carmen Ruiz-de-Azcárate, & Ángel F. Agudo-Peregrina
In the past decades, online learning has transformed the educational landscape with the emergence of new ways to learn. This fact, together with recent changes in educational policy in Europe aiming to facilitate the incorporation of graduate students to the labor market, has provoked a shift on the delivery of instruction and on the role played by teachers and students, stressing the need for development of both basic and cross-curricular competencies. In parallel, the last years have witnessed the emergence of new educational disciplines that can take advantage of the information retrieved by technology-based online education in order to improve instruction, such as learning analytics.
This study explores the applicability of learning analytics for prediction of development of two cross-curricular competencies – teamwork and commitment – based on the analysis of Moodle interaction data logs in a Master’s Degree program at Universidad a Distancia de Madrid (UDIMA) where the students were education professionals. The results from the study question the suitability of a general interaction-based approach and show no relation between online activity indicators and teamwork and commitment acquisition. The discussion of results includes multiple recommendations for further research on this topic.
Measuring and Understanding Learner Emotions: Evidence and Prospects
Bart Rienties and Bethany Alden Rivers for Learning Analytics Community Exchange (LACE)
Emotions play a critical role in the learning and teaching process because they impact on learners’ motivation, self-regulation and academic achievement. In this literature review of over 100 studies, we identify many different emotions that may have a positive, negative or neutral impact on learners’ attitudes, behaviour and cognition. We explore seven data gathering approaches to measure and understand emotions. With increased affordances of technologies to continuously measure emotions (e.g., facial and voice expressions with tablets and smart phones), in the near future it might become feasible to monitor learners’ emotions on a real-time basis.
Videos, Presentations, and Webinars
Learning Analytics: An Essential Tool for Learning in the Future
Simon Buckingham Shum