MARCH 23 , 2020 | 9 AM - 5 PM | FRANKFURT, GERMANY

WORKSHOP ON LEARNING ANALYTIC SERVICES TO SUPPORT PERSONALIZED LEARNING & ASSESSMENT AT SCALE

The 10th International Learning Analytics & Knowledge Conference

The focus of this workshop is on multidisciplinary research in the areas of personalization and adaptation of digital education and assessment tools. Recent developments and the prior instance of this workshop indicate interest in rethinking learning and assessment systems that have largely been developing separately and seldom thought of as complimenting parts of a unified Learning Assessment System (LAS). Such compartmentalization resulted in incremental improvement of the systems we have. The educators often rely on formative assessments (e.g., weekly quizzes) that operationally reflect upon overall classroom standing with respect to conceptual mastery and studentsā€™ relative progress. There is also a growing interest in performance assessments and learning that are individualized and adaptive and are carried out in a standardized ubiquitous manner. Traditional approaches are unable to fully explain why students perform as they do and are not yet suited to measure increasingly important constructs like behavior, affect, or collaboration.

The field at large desires to make progress towards LASs that are educationally effective, reflect realistic educational goals, accommodate student collaboration, and provide reliable instructional support for teachers. The early attempts to create such systems demonstrate great potential. However, these LASs come with many challenges in terms of measurement, operation, and unification and standardization. Recent advances in applied machine learning (ML) offer opportunities to address these challenges by aggregating and analyzing the Big Data that is accumulated when students interact with LASs. Among other approaches are those that structure data into various forms of learner record stores, align instructional content and the assessment content across theoretically or empirically defined knowledge component schema and standards such as the Common Core State Standards or the New Generation State Standards. Analytical platforms and service providers that offer operational and posthoc investigation support for adaptation of learning paths and assessment delivery.

This workshop would be in its second iteration following a successful execution at LAK 2019 in Arizona where it was sold out. It provides a venue for researchers that have been working on multiple components of LASs for a long time to share their experience and their findings in the area of framework building and scaling the personalization and adaptation approaches. This time, we would like to have an open submission process and, while encouraging a group of teams to submit, let a wider population of researchers contribute. We are reserving an option to have several invited keynotes as well. We will focus on finding the common ground between the approaches presented and would work toward advancing the agenda of LASs further.

Learning Analytics & Knowledge Conference
Goethe University
Frankfurt, Germany

ORGANIZERS

The focus of this workshop is on multidisciplinary research in the areas of personalization and adaptation of digital education and assessment tools. The organizing committee includes experts from fields of educational measurement, computational psychometrics, and adaptive testing (Alina von Davier), intelligent tutoring systems (John Stamper & Steve Ritter), machine learning and adaptation methods in education (Michael Yudelson & Peter Brusilovsky). These scientists bring many years of experience and deep knowledge from their respective fields and are passionate about making connections across disciplines. They are actively involved in several research initiatives that explore new forms of teaching and assessment tools that combine research from both machine learning and educational measurement fields.

There is also a growing interest in performance assessments and learning that are individualized and adaptive, and efforts are being made to develop these technologies in a ubiquitous manner. Traditional approaches are largely unable to explain why students perform as they do and are unsuited to measure increasingly important constructs like behavior, affect, or collaboration. It is also essential to make progress towards LASs that are educationally effective, reflect realistic educational goals, accommodate student collaboration, and provide reliable instructional support for teachers.

Early attempts to create such systems demonstrate great potential. However, these LASs come with many challenges in terms of measurement, operational, and unification and standardization. Recent advances in applied machine learning (ML) offer opportunities to address these challenges by aggregating and analyzing the Big Data that is produced when students interact with LASs. Among other approaches are those that structure data into various forms of learner record stores, align instructional content and the assessment content across theoretically or empirically defined knowledge component schema and standards, such as the Common Core State Standards or the ACT Holistic Framework, analytical platforms and service providers that offer operational and investigational support for adaptive products and the process of content and assessment delivery.

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Peter Brusilovsky University of Pittsburg

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John Stamper Carnegie Mellon University

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Steve Ritter Carnegie Learning, Inc.

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Alina von Davier ACTNext

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Michael Yudelson ACTNext

SUBMISSION AND REVIEW

ACTNext will create and maintain the workshop website that will sustain well after the workshop is over. Submissions will be accepted online. Questions should be directed to Michael Yudelson (michael.yudelson@act.org) with the subject set to "LAK 2020 Adaptive Engines Workshop". All submissions will be judged on their novelty, conceptual and opinionated reflection on the topic of the workshop, and potential impact on the adaptive and personalized delivery of educational content and assessment.
The length of your submission should be 6-10 pages in the format defined by LAK conference here https://lak20.solaresearch.org/submission-guidelines#prepareWorkshop.

SCHEDULE

The workshop will be in the form of Symposium and is intended as full-day with an estimated number of 8-12 oral presentations (openly submitted and invited keynotes). The organizers will moderate the course of the workshop as well as emerging discussions. Organizers will provide an introduction to the workshop, will lead the discussion after each oral presentation, and summarize the workshop. Workshop attendees will be actively involved in post-presentation Q&A and other discussions throughout the day. The workshop will follow an open attendance model: any conference delegate may register to attend. Each speaker will present their ongoing research and will give a brief overview of state-of-the-art methods and applications in their respective fields.

Concrete schedule TBD.

STUDENT TRAVEL SUPPORT

SPLICE group made available five $500 stipends for travel expenses to students coming from USA. Inquire with Michael Yudelson (michael.yudelson@act.org) to know more.

INTENDED OUTCOMES

We believe multidisciplinary research and collaboration are key to developing the next generation learning and assessment systems that amass a critical set of adaptive support methods to cater to student needs and bring the sophistication and pedagogical nuances of a good teacher. This workshop would provide a forum for the sharing of knowledge and ideas across disciplines including computational psychometrics, adaptive learning and testing, and learning analytics, machine learning, educational measurement, and natural language processing. The research is relevant and timely for advances in learning and performance assessment simulation systems and collaborative LASs. We expect that by bringing together some of the best minds in these fields, we will be able to further the state of the art and generate an increasing interest and excitement in this area.

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