Computational Psychometrics Archives

Jul12024 by Sebastian GombertNo Comments

New pub: Predicting Item Difficulty and Item Response Time with Scalar-mixed Transformer Encoder Models and Rational Network Regression Heads

Artificial Intelligence, Assessment, Computational Psychometrics, Conference, Higher Education, Publication, Workshop

In a contribution to the BEA 2024 Shared Task, we addressed the challenge of predicting the difficulty and response time of multiple-choice questions from the United States Medical Licensing Examination® (USMLE®). This exam is an important assessment for medical professionals. To predict these variables, we evaluated various BERT-like pre-trained transformer models. We combined these models with Scalar Mixing and two custom 2-layer classification heads, using learnable Rational Activations as the activation function. This multi-task setup allowed us to predict both item difficulty and response time. The results were noteworthy. Our models placed first out of 43 participants in predicting item difficulty and fifth out of 34 participants in predicting item response time. This demonstrates the potential of advanced AI techniques in improving the evaluation processes of critical exams like the…

Apr112024 by Sebastian GombertNo Comments

Team led by Sebastian Gombert wins one of two tracks at BEA 2024 shared task on predicting Item Difficulty and Item Response Time

Artificial Intelligence, Assessment, Award, Computational Psychometrics, Conference, Higher Education, New Pub, Workshop

For standardized exams to be fair and reliable, they must include a diverse range of question difficulties to accurately assess test taker abilities. Additionally, it's crucial to balance the time allotted per question to avoid making the test unnecessarily rushed or sluggish. The goal of this year's BEA shared task (competition) was to build systems which could predict Item Difficulty and Item Response Time for items taken from the United States Medical Licensing Examination (USMLE). EduTec member Sebastian Gombert designed systems which are able to predict both variables simultaneously. These placed first out of 43 for predicting Item Difficulty and fitfth out of 34 for predicting Item Response Time. They use modified versions of established transformer language models in a multitask setup. A corresponding system description paper titled Predicting Item…

Jan292024 by Sebastian GombertNo Comments

New Pub: From the Automated Assessment of Student Essay Content to Highly Informative Feedback: a Case Study

Artificial Intelligence, Assessment, Computational Psychometrics, Empirical Study, Feedback, Higher Education, Journal, Publication, Special Issue, Technical paper

How can we give students highly informative feedback on their essays using natural language processing? In our new paper, led by Sebastian Gombert, we present a case study on using GBERT and T5 models to generate feedback for educational psychology students. In this paper: ➡ We implemented a two-step pipeline that segments the essays and predicts codes from the segments. The codes are used to generate feedback texts informing the students about the correctness of their solutions and the content areas they need to improve. ➡ We used 689 manually labelled essays as training data for our models. We compared GBERT, T5, and bag-of-words baselines for both steps. The results showed that the transformer-based models outperformed the baselines in both steps. ➡ We evaluated the feedback with a learner cohort…

Dec42023 by Prof. Dr. Hendrik DrachslerNo Comments

16th eLearning Netzwerktag: An Insightful Recap of the Fast-Paced Year

Artificial Intelligence, Assessment, Augmented Reality, Competence development, Computational Psychometrics, Computer-supported collaborative learning, Conference, Event, Feedback, Gender, Higher Education, Learning Analytics, Learning Design

The annual eLearning Netzwerktag was a highly anticipated one-day event where the eLearning community of Frankfurt and the surrounding areas gathered to present the highlights of the past year to the public. On November 21, 2023, the event took place at Campus Westend, Goethe University Frankfurt am Main. Among the speakers, the Prof. Dr. Maren Scheffel, Prof. Dr. Franziska Matthäus , CIO of Goethe University Ulrich Schielein, Prof. Dr.Hendrik Drachsler, Director of studiumdigitale, delivered an opening speech that reflected on an incredible year, with a particular focus on the advancements in generative Artificial Intelligence applications. Hendrik Drachsler's speech highlighted the significant developments in the field of digital learning. At the previous Netzwerktag, applications like ChatGPT, Midjourney, Stablediffusions, and open language models (LLMs) such as LAMA were relatively unknown to most…

Jul102023 by Heather WehnerNo Comments

Dr. Eyal Rabin from the Open University of Israel joins EduTec group and GU as an International Visiting Fellow

Computational Psychometrics, Learning Analytics, Research Methods

We are delighted to announce that Dr. Eyal Rabin, a distinguished researcher in the field of educational technology, has joined us as an International Visiting Fellow at the EduTec group at DIPF and Goethe University in Frankfurt from July till September. This fellowship is generously funded by the Goethe University and aims to foster collaborative research and knowledge exchange in the field of educational technology. Dr. Rabin serves as a research associate at the Center of Innovation in Educational Technology at the Open University of Israel. His research expertise lies in exploring the complexities of learning in online courses and digital environments, employing learning analytics methods (LA) and drawing from multiple interdisciplinary fields, including psychology, education and computer science. The focus of Dr. Rabin's research revolves around understanding the factors…

Jun22023 by Heather WehnerNo Comments

New pub: Digitalisierung und Diagnostik in Schulen – Herausforderungen für Bildungspraxis und Bildungsforschung

Assessment, Book chapter, Computational Psychometrics, Digitalisation, Learning Analytics, Research Methods, Research topic, School

In the spring of 2020, schools faced an unprecedented challenge as the pandemic disrupted traditional modes of instruction and school development. With on-site learning replaced by digital formats and distance communication, educators had to quickly adapt to the new normal. Amidst these changes, the field of education encountered specific challenges related to digital school management, digital learning, and assessing learning progress. Particularly, computer-aided diagnostics emerged as a valuable tool for gaining insights not only into learning outcomes but also into the learning process itself. Researchers became intrigued by the potential of digital media in shaping learning experiences and how the resulting data could be effectively utilized in educational practice. This paper explores the current challenges and potentials in computer-based, learning-accompanying diagnostics. The primary hurdles involve implementing suitable instruments within schools…

May152023 by Prof. Dr. Hendrik DrachslerNo Comments

New research program: Towards Highly Informative Learning Analytics

Artificial Intelligence, Assessment, Book, Computational Psychometrics, Computer-supported collaborative learning, Feedback, Further Education, Higher Education, Keynote, Learning Analytics, Learning Design, Research Methods, School

On May 12, 2023, the Highly Informative Learning Analytics (HILA) research program of the EduTec@DIPF, studiumdigitale@Goethe University Frankfurt and the Open Learning and Instruction group@Open Universiteit was presented by Hendrik Drachsler at the main campus of the Open University of the Netherlands. The release of the HILA research program marks a significant milestone for the collaboration in the field of learning analytics between of the Dutch-German research collective. The HILA research program is focused on developing new tools and methods to collect, analyze, and interpret data that can help educational institutions to understand the learning process better. As part of the program's launch, a keynote by Ioana Jivet on student-facing learning analytics was provided. Ioana reported on two empirical studies investigating the effect of data-driven feedback on students. [pdf-embedder url="https://edutec.science/wp-content/uploads/2023/05/2023_05-Keynote-Symposium-Hendrik.pdf"…

Aug262022 by Prof. Dr. Hendrik DrachslerNo Comments

New Pub: Toward learning progression analytics — Developing learning environments for the automated analysis of learning using evidence-centred design

Computational Psychometrics, Journal, Learning Analytics, Learning Design, Open access, Project, Publication, School

[caption id="attachment_4319" align="alignright" width="450"] A procedure for developing digital learning environments that allow for the automated assessment of learning.[/caption] National educational standards stress the importance of science and mathematics learning for today’s students. However, across disciplines, students frequently struggle to meet learning goals about core concepts like energy. Digital learning environments enhanced with artificial intelligence hold the promise to address this issue by providing individualized instruction and support for students at scale. Scaffolding and feedback, for example, are both most effective when tailored to students’ needs. Providing individualized instruction requires continuous assessment of students’ individual knowledge, abilities, and skills in a way that is meaningful for providing tailored support and planning further instruction. While continuously assessing individual students’ science and mathematics learning is challenging, intelligent tutoring systems show that it…

Mar302022 by Prof. Dr. Hendrik DrachslerNo Comments

Keynote at LERN Jahrestagung 2022

Computational Psychometrics, Higher Education, Invited talk, Keynote, Learning Analytics, Learning Design, School

On 30 March 2022, Hendrik Drachsler gave an invited keynote at the LERN conference 2022 where he reported on the latest research on data-driven high informative feedback in higher education and schools. The talk focused on the experience of edutec.science research collective that has been gained in the projects DIFA, HIKOF-DL, AFLEK and ALICE. The presentation provided an overview of actionable and supportive feedback to learners as well as the various technical products that the EduTec group has developed. It, therefore, applies web technology to support meta-cognitive and collaborative learning skills with high-informative feedback methods. Hendrik applies validated measurement instruments from the field of psychometrics and investigates to what extent Learning Analytics interventions can reproduce the findings of these instruments. He discussed the lessons learned from implementing TLA systems. He…

Jan252022 by Sebastian GombertNo Comments

Team of EduTec and TBA Members Wins Runners-Up Prize @ NAEP Reading Automated Scoring Challenge

Artificial Intelligence, Assessment, Award, Computational Psychometrics, School

The NAEP Reading Automated Scoring Challenge was a competition which was held in late 2021 by the National Center for Education (USA). The goal was to evaluate the applicability of natural language processing methodology to the task of scoring of large scale constructed response assessment data. In addition to this, participating models were also required to be interpretable and free of algorithmic bias against different student demographics. The data set which was used to evaluate the systems consisted of responses from 4th and 8th grade school student to 20 different reading comprehension tasks. More than a dozen different teams from universities and private assessment companies submitted contributions. Out of these, 12 contributions, including ours, were selected as eligible with respect to interpretability and algorithmic fairness. These contributions were then ranked…