We are pleased to present the following candidates as nominees for election to the SoLAR Executive. All SoLAR individual and students members are eligible to vote for all positions. Links to access the online voting system will be sent to SoLAR members via email.
Candidates for SoLAR Executive Member at Large
(8 Candidates, 6 Positions Available)
Associate Head of Teaching & Learning and Senior Lecturer, School of Electrical and Information Engineering
Interest in Learning Analytics: I am a researcher in Educational Technology and the area of Learning Analytics is one of my main interests together with personalization and learning design.
Biography: I obtained my PhD in Computer Science by the University of Colorado at Boulder. I am thedirector of the Learning and Affect Technologies Engineering laboratory specialized in the design of adaptive and personalized software systems for learning. My areas of research are learning analytics, software tools for collaboration and personalized learning processes, and software systems to improve teaching practices and student outcomes. I have participated in national and international projects funded by the Office for Teaching and Learning (Australia), National Science Foundation (USA), and the European Union. I serve as member of the editorial boards of the IEEE Transactions on Learning Technology and the Journal of Social Media and Interactive Learning Environments, and as associate editor of the Journal of Learning Analytics.
Open University of the Netherlands, Welten Institute
Interest in Learning Analytics: I am interested in awareness and reflection support including personalization and visualization technologies as well as recommender systems for learning. I am also interested in evaluating the effects of technological innovations under controlled conditions and therefore care about sharing of educational datasets and technologies to make LA research more comparable and reproducible.
Biography: Hendrik Drachsler studied educational sciences and computer sciences at the University of Duisburg, Germany. During his studies (2002) he work as developer for a medical spin-off from the Fraunhofer Gesellschaft called LOCALITE where he developed a knowledge management tool for a navigation system for knee prosthetics. The tool was used for an online user support system, to create the software manual, and to create quality tests for the navigation system based on ISO 9001 standard. In 2004 Hendrik started his academic career as research assistant at the Fraunhofer Institute for Applied Information Technology (FIT). He was granted by the Friedrich-Ebert-Stiftung to extend his research on Technology-Enhanced Learning. At FIT he participated in the development of a Hard- and Software simulator for transesophageal echocardiography. His Master thesis on sensorimotor and mental model training of medical professionals in transesophageal echocardiography was completed in May 2006 and was qualified as outstanding.
In April 2006 Hendrik joined the Open University of the Netherlands where he conducted his PhD in the European funded Project TENCompetence (6th Framework Programme) on ‘Navigation Support for Learners in Informal Learning Networks. After his PhD he coordinated and contributed to various EU projects in the domain of Technology-Enhanced Learning In this context, he has led different research groups and PhDs and developed various software applications and evaluated them with participative design approaches by applying a combination of computer and social science methods like structured interviews, questionnaires, writing personas, usability studies (SUS & eye tracking), group concept mapping, PMI rating, TAM and A/B testing. This has lead to high recognition within the community and highly cited research articles
Hendrik is currently Assistant Professor at the Open University of the Netherlands and principal investigator of two European projects He is a member of SoLAR and EATEL and leading the SIG dataTEL and the SURF SIG Learning Analytics At LAK, he is known for chairing the Linked Data for Learning Analytics Workshop (LALD 2011), the LAK data competition 2013, 2014, 2015 conferences.
Program Director – Evaluation and Learning Analytics – Faculty of Arts, The University of British Columbia
Interest in Learning Analytics: I am currently completing my second year as a member of the SoLAR Executive, and now have co-responsibility for the Communications portfolio. Because it takes to time to become familiar with the structures and processes of an organization like SoLAR, I feel that it is this year that I have become a truly productive and contributory member. I would be really pleased to assist with Executive continuity by completing another term on the Executive and sustaining and growing our organization and practices. I am especially interested in working to bridge the gap between learning analytics research and practice.
Biography: In the Faculty of Arts at UBC I lead a variety of learning analytics and academic analytics projects with the goal of illuminating existing challenges and persuading decision-makers (from individual educators to senior administrators) of the rich information available in existing educational data sets, and the value of mining these to better inform planning at many levels, from learning design through curriculum planning to more effective targetting of learner support and advising. I make heavy use of visual analytics tools and approaches, and have established active collaborations with the Vancouver Institute for Visual Analytics (VIVA).
I hold graduate degrees in the Sciences (UBC) and the Social Sciences (Simon Fraser University), and have undertaken interdisciplinary qualitative and quantitative educational research over the past fifteen years, with a particular interest in eLearning. I have also designed and taught courses for UBC Continuing Education, the UBC Integrated Science program, the UBC Department of Sociology, and most recently UBC’s Masters in Educational Technology program. After holding positions in UBC Continuing Studies and the UBC Faculty of Science, I am now Program Director for Evaluation and Learning Analytics in the Faculty of Arts.
My current analytic interests are focused on analyzing and visualizing temporal (time-sequence) aspects of educational data, and on developing useful analyses and representations of themes in unstructured data (course evaluation comments. In addition, my experience of the challenges of implementing learning analytics in our large institution has pushed me to write and think about strategic approaches for implementing learning analytics at scale.
Moray House School of Education, University of Edinburgh
Interest in Learning Analytics: I am currently completing my second year as a student member of the SoLAR Executive Committee, and now have co-responsibility for the Website portfolio. Within these two years I had an opportunity to participate in numerous activities conducted by the Society and learn about the processes within SoLAR. Since I took over the responsibility for the Website portfolio, we did a considerable work to maintain and, where possible, improve the quality of the SoLAR web presence. We also made plans how the web support activities should be carried forward. Therefore, I would be pleased to have an opportunity to ensure the continuity and progression of the initiatives organized within the Website portfolio.
Biography: I am currently finalizing my PhD dissertation under the supervision of Professor Dragan Gašević, Professor Sian Bayne from the University of Edinburgh, and Professor Marek Hatala from the Simon Fraser University. I expect to graduate by May 2017 with a PhD in education with a focus on learning analytics. My research primarily centers on studying professional learning, observed through the lens of networked learning theory. As such, I study massive open online courses as one of the prominent approaches for supporting professional learning in digital non-formal educational settings. Developing theory-driven data analytics models for assessing the quality of learnig in computer mediated context, my research i) generates insights into factors that promote effective collaborative learning and ii) informs the design of digital environments in which collaborative learning occur.
I have a strong publication record being author or co-author on more than 30 studies published in top journal and peer-reviewed conference venues related to the fields of learning analytics, educational data mining, and learning technologies. My work has received considerable recognition in the international research community through several best paper awards, scholarships, and stipends received. Moreover, I have been actively involved in the organization of the 6th International Conference on Learning Analytics and Knowledge (LAK 2016), as a local chair. Finally, I was part of the team that prepared Learning Analytics Summer Institute (LASI) 2016 that was held at the University of Michigan in June 2016.
Thompson Rivers University
Interest in Learning Analytics: I initially became interested in Learning Analytics in 2010 when I learned that data could be used to challenge beliefs about learning and training and improve performance. I went on to learn more about learning analytics while completing an MEd at Athabasca University and wrote an early literature review of what a new field at the time. Over the next several years, I undertook several data-supported learning initiatives that involved redesigning a series of educational programs and correlating test scores to performance outcomes. By 2014, the learning experiences of over 10,000 employees had been positively impacted by the use of learning and performance analytics.
Biography: In 2014, I moved to Thompson Rivers University’s Open Learning division where I am working on a series of projects again seeking to challenge beliefs about learning and learning design using data. The data comes from a variety of sources including student information systems, LMSs, xAPI, open tools and student course evaluations. Of particular interest to me is the possibility of connecting open pedagogy, tools, data, analysis and algorithms in a way that could empower students and while increasing their digital and data literacy.
I’ve been a strong advocate for learning analytics as an applied field that includes active engagement of practitioners and would bring that voice to the SoLAR executive. I’d work actively to engage more educational technologists, instructional designers and educators in the field of learning analytics. I expect that work would include open conversations about the benefits, risks and limitations of using data to improve learning opportunities and outcomes, sharing practical entry points for using data, and offering practical implementation support.
Interest in Learning Analytics: I’m really interested in all phases mentioned in the definition of Learning Analytics made on the 1st LAK 2011’s definition of Learning Analytics which is “The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.”. I’m interested in measuring the Learning Analytics impact using feedback loop of Design, Analyze, Intervene, Evaluate.
Design: Define analytical metrics, establish hypothesis, validate test experiments with end users.
Analyze: Collect data, build customized predictive models, visualizations.
Intervene: Research and develop the best intervention approach that leads to improve learner performance.
Evaluate: Evaluate interventions and current process and feed the evaluations as feedback to improve the design phase.
I’m interested in Predictive Learning Analytics and early intervention systems for student success. I’m interested in the change that is required at the institution to ensure that its organizational culture understands and values data-informed decision-making processes.
Biography: Shady Shehata is Principal Data Scientist and Manager of Business Intelligence and Data Science team at D2L. Shady is leading the charge on the introduction of Big data architecture to support operational initiatives, providing product feedback and supply additional market intelligence at D2L. Shady has developed new methodologies and tools to enable advanced probabilistic and predictive modeling and statistical analysis against petabyte-scale data sets leveraging massively parallel processing using Big data technologies. Shady has led the research and development of predictive analytics products at D2L. He evangelizes D2L research and development and the science behind it through journals, conference presentations, demos and patents.
Shady Shehata has been in the software industry for over 18 years. Shady has a balance of extensive experience in software design and development of algorithmic libraries and applications with strong research experience in data mining, machine learning, text mining, information retrieval on Big data and a broad set of technical skills. Shady’s doctoral work at the University of Waterloo focused on concept and semantic mining: the study of extracting important concepts that contribute to the text meaning to enhance the quality of text clustering, categorization and retrieval. Shady’s research work has been recognized and published in top conferences and journals and has received many awards.
University of Michigan
Interest in Learning Analytics: I highly value the intellectual diversity of the SoLAR membership and the signature conference (LAK) and journal (JLA) outlets. My interest in deepening my engagement through SoLAR executive membership is to help contribute more fully to this diversity, and to identify opportunities for us as a community to strengthen our inter- and multi-disciplinary roots. Sharing novel techniques, methods, and approaches across disciplines is why I consider SoLAR and LAK my core scholarly society and conference.
Biography: I’m an educational computer scientist with a research background in behavior-based learning analytics. I use a variety of data science techniques, quantitative and qualitative, to try and understand student learning both in predictive fashions (e.g. machine learning) and in explanatory fashions (e.g. information visualization). I am particularly interested in scaled learning environments (e.g. MOOCs) and those which have multi-modal data (e.g. text and behavior environments, often found in large undergraduate courses), and the educational construct I tend to focus on is learner engagement and affinity with the learning environment. I am both a Research Assistant Professor in the School of Information, and Director of Learning Analytics and Research with the University of Michigan Office of Academic Innovation.
School of Informatics, University of Edinburgh
Interest in Learning Analytics:Learning analytics has a tremendous potential to improve our understanding of human learning and to advance the current educational practices. With the SOLAR’s pivotal role in the LA field, serving on the executive committee would be a fantastic opportunity for me to contribute to the broader LA community by engaging into some of SOLAR’s excellent initiatives. In particular, given the interdisciplinary nature of learning analytics field, I see an enormous potential of Info Hub and LASI initiatives in enabling better communication between researchers from the different domains, and I would like to help their expansion and further development.
Biography: I am currently finishing my doctoral studies in Learning Analytics at the School of Informatics, the University of Edinburgh, working under the supervision of Professor Dragan Gasevic. My Ph.D. research is focused on the development of novel learning analytics methods based on the trace data collected by learning management systems and their use to improve inquiry-based online education. I also work as a part-time research assistant at the LINK research lab at the University of Texas at Arlington and data scientist for UK’s Genuine Market Research.
I authored and co-authored more than 40 publications on Learning Analytics, Educational Data Mining, MOOCs, and Educational Technology. I am also an active member of the learning analytics community; I served as a local co-chair for the LAK’16 conference, Web-chair for the L@S’16 and a program co-chair for the LWMOOCs’16 conference. I also presented at LASI’14 and LASI’16 events as well as participated in a significant number of research projects including MOOC research initiative (MRI). I was also a first author on a paper which was awarded the best paper award at the LAK’15 conference. Before my doctoral studies, I worked as a senior software engineer on the development of large distributed information systems.