AY 2018 kickoff meeting

Welcome back, everyone!

The first AIM Analytics session is consist of an introduction to events that will happen in this academic year, series of micro talks, and a community discussion. The detailed agenda is below:
  • Intro to series
  • Introducing our new reading/hacking group
    • ASSISTments Data Mining Competition
  • Micro talks
    • Benjamin Koester: Measuring Effects and outcomes of Learning Communities at UMich
    • Rohail Syed: Retrieval Algorithms Optimized for Human Learning
    • Josh Gardner: Building, Evaluating, and Replicating MOOC Dropout Models
    • Phoebe Liang: Best Answer Prediction in MOOC Discussion Forums 
    • Heeryung Choi: Understanding diversity attributes in students : From learner diversity to different opinions
    • Nia Dowell: A temporal lens: Understanding changes of MOOC learners
    • Carl Haynes: How am I doing? : Student-Facing Performance Dashboards in Higher Education
    • Rebecca Quintana:  Visualizing course structure: Just bead it!
  • Socialization and discussion

Learning Analytics: its emergence, trends, and systemic impact – Slide from George Siemens

Learning analytics as an academic research space has been growing in influence for nearly a decade. Campuses globally are deploying learning analytics to address a range of challenges including student dropout, poor engagement and targeted marketing as well as predict teaching and resource needs. As a field, learning analytics has advanced rapidly both as a research domain and as a practical on-campus activity to increase organizational use of data. In this presentation, Dr. George Siemens will explore both the research and the practice of analytics in education, focusing on the development of the Society for Learning Analytics, models for research and organizational data use and growing sophistication of data collection through psychophysiological approaches.

Dr. George Siemens researches networks, analytics, wellbeing and openness in education. Dr. Siemens is Professor and Executive Director of the Learning Innovation and Networked Knowledge Research Lab at University of Texas, Arlington and cross-appointed with the Centre for Distance Education at Athabasca University. He has delivered keynote addresses in more than 35 countries on the influence of technology and media on education, organizations and society. His work has been profiled in provincial, national and international newspapers (including The New York Times), radio and television. He has served as Principal Investigator or Co-Principal Investigator on grants totaling more than $15 million, with funding from the National Science Foundation, Social Sciences and Humanities Research Council (Canada), Intel, Bill & Melinda Gates Foundation, Boeing, and the Soros Foundation. He has served as a collaborator on international grants in European Union, Australia, Senegal, Ghana, and United Kingdon. He has received numerous awards, including honorary doctorates from Universidad de San Martín de Porres and Fraser Valley University for his pioneering work in learning, technology and networks. He holds an honorary professorship with University of Edinburgh and adjunct status with University of South Australia.

Dr. Siemens is a founding President of the Society for Learning Analytics Research. He has advised government agencies in Australia, European Union, Canada and United States, as well as numerous international universities, on digital learning and utilizing learning analytics for assessing and evaluating productivity gains in the education sector and improving learner results. In 2008, he pioneered massive open online courses (MOOCs). He blogs at and on Twitter (@gsiemens).


Accessing Educational Datasets at Michigan – Slides from the panel discussion

Panel: Accessing educational datasets at Michigan: privacy, policy, security, legal, and ethical considerations and responsibilities.

Join us on November 7th at 12 p.m. in the Hatcher Gallery Lab for a panel and Q&A with Maya Kobersy (U-M Associate General Counsel),  Sol Bermann (University Privacy Officer), Cindy Shindledecker (IRB Director) and Mike Daniel (Director of Policy for Academic Innovation) to understand how to access and responsibly use educational data at the University of Michigan. Suitable for all faculty, postdocs, researchers and students who are looking to use educational data, this panel will provide insight into the “how,” “who” and “why” of educational data at U-M and plenty of time will be left to ask questions of these experts. A light lunch is provided.

Questions covered include:

1) How does an exemption determination from the Internal Review Board (IRB) for research involving “normal educational practices” differ from a standard IRB approval?

2) What does Family Educational Rights and Privacy Act (FERPA) mean to the researcher, and how does the research ensure their work complies with U-M FERPA requirements?

3) Who are the data stewards, and how do you find the right person to ask for educational data?

4) What are best practices for de-identifying data? What is the difference between de-identifying data and anonymizing data?

5) What privacy and ethical considerations and best practices should I be thinking about?

6) What data security practices do I need to follow and/or should I consider?

Please RSVP here


AIM Analytics talk series – Nia Dowell

Nia Dowell from the University of Memphis will provide a talk on October 24, Monday, at 12:00-1:30 pm in 2435 North Quad.


If you are planning to attend, please RSVP. More details are listed below.


Title: Group communication analysis: A computational-linguistic framework for exploring conversational roles in online multi-party communication



This talk will present results from recent work that uses language to assess social dynamics during collaborative interactions. I will introduce group communication analysis (GCA), a novel approach for detecting emergent learner roles from the participants’ contributions and patterns of interaction. This method makes use of automated computational linguistic analysis of the sequential interactions of participants in online group communication to create distinct interaction profiles. We have applied the GCA to several collaborative learning datasets. Cluster analysis, predictive, and hierarchical linear mixed-effects modeling were used to assess the validity of the GCA approach, and practical influence of learner roles on student and overall group performance. The results indicate that learners’ patterns in linguistic coordination and cohesion are representative of the roles that individuals play in collaborative discussions. More broadly, GCA provides a framework for researchers to explore the micro intra- and inter-personal patterns associated with the participants’ roles and the sociocognitive processes related to successful collaboration.

Bio: Nia Dowell is a cognitive psychology doctoral candidate at the Institute for Intelligent Systems in the University of Memphis. Nia is currently pursuing her PhD under the mentorship of Professor Arthur Graesser. Her primary interests are in cognitive psychology, discourse processing and learning sciences. In general, her research focuses on using language and discourse to uncover the dynamics of socially significant, cognitive, and affective processes. She is currently applying computational techniques to model discourse and social dynamics in a variety of learning environments including teacher education programs, intelligent tutoring systems (ITSs), small group computer-mediated collaborative learning environments, and massive open online courses (MOOCs). Her research has also extended beyond the educational and learning sciences spaces and highlighted the practical applications of computational discourse science in the clinical, political and social sciences areas.

Continue reading AIM Analytics talk series – Nia Dowell

AIM Analytics talk series – Vitomir Kovanovic

Vitomir Kovanovic from University of Edinburgh will provide a talk on Octover 10, Monday, at 12:00-1:30 pm in the Hatcher Gallery Lab.
If you are planning to attend, please RSVP. More details are listed below.


A Novel Model of Cognitive Presence Assessment Using Automated Learning Analytics Methods.


One of the significant trends in educational is the increased interest in the development of students’ critical and deep thinking skills. Besides creativity, collaboration, and communication, critical thinking has been recognized as one of the core 21st-century skills necessary to work in the globalized economy. One of the widely used approaches for the development of critical thinking skills is inquiry-based learning, which — instead of presenting facts and information in a smooth learning path — begins with a question, problem, or scenario, and students build knowledge through interaction with the learning content and other students. In the context of online learning, the Community of Inquiry (CoI) model is a widely used pedagogical framework that outlines the constructs that shape students’ overall learning experience, including cognitive presence, which captures the development of students’ critical and deep thinking skills. Although cognitive presence has been recognized as important in student learning outcomes, assessing it is challenging, primarily because of its latent nature and the physical constraints of online learning settings. However, the vast amounts of data collected by the learning systems provide opportunities to assess student levels of cognitive presence through automated data analytics techniques, often referred to as learning analytics. In this presentation, we will overview a framework for the formative assessment of student cognitive presence based on learning analytics methods.  Those include automatic analysis of student discussions and profiling of students based on their use of the available learning systems. With the goal of providing both instructors and students with timely and actionable feedback, the developed tools also enable to better understand the overall complexity of learning, thus advancing both the practice and theory of online learning.


Vitomir Kovanović is a Ph.D. student and research assistant at School of Informatics, University of Edinburgh, United Kingdom, and a research assistant at the Learning Innovation and Networked Knowledge Research Lab at the University of Texas, Arlington. Vitomir’s research is in the area of Learning Analytics and Educational Data Mining focuses 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. He authored and co-authored several book chapters, conference papers, and journal articles. Vitomir is a recipient of two best paper awards (LAK15 and HERDSA15 conferences) and scholarships by the Serbian Ministry of Education, Simon Fraser University, and the University of Edinburgh.

AIM Analytics talk series – Marco Molinaro

Marco Molinaro from UC Davis will provide a talk on September 12, Monday, at 12:00-1:30 pm in the Hatcher Gallery.
If you are planning to attend, please RSVP.  More details are listed below.


Marco Molinaro, Ph.D., is the Assistant Vice Provost for Educational Effectiveness at UC Davis where he oversees the Center for Educational Effectiveness which includes learning and teaching support, instructional research and development and educational analytics. Dr. Molinaro has over 20 years of educational experience creating and leading applications of technology for instruction, scientific visualization and simulation, tools for evidence-based instructional actions, curriculum development and evaluation, and science exhibits for students from elementary school through graduate school and for the general public.

Currently, Molinaro is leading the UC Davis university-wide effort to improve undergraduate student success through the Center for Educational Effectiveness (an expansion of the former iAMSTEM Hub merged with the prior Center for Excellence in Teaching and Learning.) As part of the effort, the Center is working with faculty and staff across the university to: 1) improve and evolve the introductory undergraduate curriculum, 2) understand and measure change with new analytics tools and approaches that guide instructional improvement and, 3) develop actionable student success models.

Molinaro is also the founder of the Tools for Evidence-based actions community, a group of researchers and administrators from over 70 universities dedicated to sharing tools and methodologies that encourage evidence-based instructional actions. His projects have been funded through the NSF, NIH and various private foundations such as Gates, Intel and the Helmsley Trust.