Attendees

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Alison Mroczkowski – Museum of Science and Industry, Chicago


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Camillia Matuk – New York University

Camillia Matuk is Assistant Professor of Educational Communication and Technology at New York University. One aspect of her work explores the design and impact of playful, STEAM-based learning environments on youths’ dispositional growth. A data set she wishes to explore during this workshop consists of survey responses, interviews, and recorded conversations among middle school youth teams during their week-long design of tabletop role-playing games based on their reading of a comic book about the science of viruses. She hopes to investigate the specific roles of fictional worldbuilding, collaboration, and the design process in promoting youths’ disciplinary thinking, interests and engagement.


Chi Un Lei – University of Hong Kong


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David Joyner – Georgia Tech

Our dataset consists of a couple thousand course reviews written by students with the dual purpose of (a) providing their feedback on the course and (b) advising future students on the course. We would like to leverage this data to understand the characteristics students use to derive their opinions of a course’s rigor and quality, the factors that contribute to a course’s workload, and the types of information students find pertinent to communicate to future students.


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Diler Oner – Boğaziçi University

I am an associate professor at the Department of Computer Education and Educational Technology, Bogazici University in Istanbul.  I am interested in assessing the development of preservice teachers’ technological pedagogical content knowledge (TPACK) using ENA.  I developed an epistemic game last summer at the Epistemic Analytics Lab for preservice teachers to improve their TPACK, and have been collecting data using that game. I would like to explore how ENA could allow me to measure TPACK development.


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Edith Bouton – Hebrew University of Jerusalem

My current research focuses on university students’ utilization of social networks based study groups, which operate without knowledge or awareness of faculty members. Some of the questions we looked into were – what are the motivations to share, who are the prominent sharers, whether or not they use these tools to deepen their engagement with the learned material via learning dialog or only use it to share and use learning artifacts. I also hope to use this workshop to learn how to build a tool that will detect and visualize true learning dialogues among students, to be used in future projects.


 

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Eric Hamilton & Seung Bok Lee – Pepperdine University

A digital makerspace community known as International Community for Collaborative Content Creation (IC4) consisting of fifteen clubs in Kenya, Finland, Namibia, and the United States involves participants, ages 10-19, who create videos and other digital artifacts to teach their peers science and mathematics. Each artifact represents a collaboration of participants from different countries. Our data is focused on participants’ socio-affective and academic development as they collaborate across cultural, economic, and international boundaries. We are using Epistemic Network Analysis (ENA) to depict important malleable variables – and the relationships between those variables – such as self-efficacy, personal identity, confidence, awareness of others, and self-awareness. Our previous work has focused on the efficacy of ENA to model and understand the salient aspects of international collaboration in digital maker spaces. Initial work has focused on interview data, but we hope to expand into records of face to face club meetings and more importantly, global meetups between intra, and international clubs.

Hiroyuki Masukawa – University of Sacred Heart, Tokyo


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Kamila Misiejuk – University of Bergen – Norway

I am a PhD candidate at the Centre for the Science of Learning and Technology (SLATE), University of Bergen, Norway. In my research I explore the potential of learning analytics to determine the quality of peer assessment. My dataset comprises text data, from a commercial peer assessment tool, coming from a variety of high schools and higher education institutions. So far, I have applied various NLP techniques, such as sentiment analysis, on the dataset, but I would like to try the Epistemic Network Analysis to gain new insights.


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Melanie Peffer & Emmy Royse – University of Northern Colorado

Our lab is interested in assessing student’s epistemological beliefs about science via their practices in simulated authentic science inquiry. We would like to learn how to use a quantitative ethnography approach to analyze student inquiry practices. We are also interested in meeting potential collaborators who work in learning analytics/big data and leverage those insights to improve classroom practice.


Nadav Ehrenfeld – Vanderbilt University

Nadav’s research team’s data include math lessons from middle and high schools in California. He is currently looking into students collaboration in groups, and in particular in the ways teachers are taking part in such conversations to elevate mathematical talk and conversational norms. Nadav is also interested in learning more about these talks (discursively and content-wise) and about the teacher’s role in them.


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Nora’Ayu Ahmad Uzir & Wannisa Matcha – University of Edinburgh

We are exploring on how student learning unfolds across an implementation of a flipped classroom course run using a learning management system. Three perspectives of learning that we are interested in are time management, learning strategies and learning topics. We aim to use Epistemic Network Analysis to explore how these three elements are associated and if there are differences across time and different group of students. Our dataset is comprised of trace data based on students’ learning actions in different time periods, collected from the learning management system.


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Ritsuko Oshima – Shizuoka University &  Jin Michael Splichal – University of Helsinki

Our datasets consist of two small groups’ discourse data of face-to-face collaboration on a science topic in high school, human immunity system. We focus on examining and understanding how student groups create and advance knowledge. By using ENA, we attempt to identify and compare each group’s characteristics of shared epistemic agency.


Sagit Betser – University California, Davis


SallyWan_pixSally Wai-Yan Wan – Chinese University of Hong Kong


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Yanghee Kim – Northern Illinois University

In the project IDEAL (Inclusive Design for Engaging All Learners), we examine the use of a sociable robot to mediate collaborative interactions among kindergarten-aged children. We implement a socio-technical triad of a robot, a child from a Spanish-speaking family, and a child from an English-speaking family, where the children work together to help the robot Skusie to learn about life on earth. IDEAL has generated the utterances made by the children, Skusie, and an adult moderator. From the transcripts of the utterances, we are interested in finding out i) to what extent this triadic learning community might help children with building common ground, equitable partnerships, and co-cultural schemas, which establish the condition for equitable intercultural collaboration, ii) what actions and/or behaviors of Skusie may promote or hinder children’s collaborative interactions and participation in the community.


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Yi-Shan Tsai – University of Edinburgh

The field of learning analytics (LA) with its associated methods of online student data analysis holds great potential to address the challenges confronting European higher education institutions (HEIs). While the use of LA has gained much attention and has been/is being adopted by many HEIs in Europe and the world, the maturity levels of HEIs in terms of being ‘student data informed’ are only in the early stages. The SHEILA Project aims to build a policy development framework by taking advantage of direct engagement of stakeholders in the development process. Our previous work has focused on looking into interests and concerns about learning analytics among different stakeholders. We hope to explore our interview data further using Epistemic Network Analysis to identify different priorities for learning analytics among European higher education institutions.


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This Could Be you

We will share a brief descriptions of participants datasets and what they hope to get out of the workshop.

 

 

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