April 2024 - EduTec Science

Apr172024 by Jane YauNo Comments

GREAT project presentation at World Forum Women in Science – Theme “Science for the SDGs”

On 15 April, GREAT project manager Dr. Jane Yau had the pleasure of moderating the session Technology, Sustainability and Industry with Prof. Nova Ahmed at the World Forum Women in Science - Theme: Science for the SDGs (https://women-in-science-without-borders.network/world-forum-women-in-science-2024/). The session included a number of initiatives of empowering women and underrepresented groups to take on science activities and careers to advance the SDGs. Jane also shared the GREAT project findings in this session with a talk “Gaming for Change: Leveraging digital games to address climate change”, based on the GREAT project methodology and first case study findings! The session was free to attend and was live-streamed on Facebook. The video recording will be available shortly.Jane will also be in Rome, Italy, on 19 April to attend the in-person Networking Event as…

Apr162024 by Heather WehnerNo Comments

New Pub: Feedback sources in essay writing: peer-generated or AI-generated feedback?

Artificial Intelligence, Empirical Study, Feedback, Further Education, Journal, Publication

A newly published article discusses the use of peer feedback as a learning strategy, particularly in large classes where teachers face heavy workloads. For complex tasks like writing argumentative essays, peers may struggle to provide high-quality feedback due to the cognitive demands involved. The emergence of Artificial Intelligence (AI) tools, like ChatGPT, raises the question of whether AI can serve as a new feedback source for such tasks. To investigate this, a study compared ChatGPT-generated feedback with peer feedback on argumentative essays written by 74 graduate students from a Dutch university. The study collected essay data, peer feedback and ChatGPT-generated feedback, and then analyzed them using coding schemes. Results showed significant differences between ChatGPT and peer feedback, with ChatGPT offering more descriptive feedback while peers focused on identifying essay problems.…

Apr152024 by Dana KubeNo Comments

New Publication: Addressing gender in STEM classrooms: The impact of gender bias on women scientists’ experiences in higher education careers in Germany

New Pub

In an expert study conducted in Germany, Dana Kube and her research team delve into the complex dynamics of gender bias within STEM (Science, Technology, Engineering, and Mathematics) classrooms. The study, aimed at understanding the role gender plays in shaping the experiences of women scientists in higher education, sheds light on the challenges they face and proposes strategies for fostering gender inclusivity in STEM classrooms. The primary objective of the study was two-fold: first, to comprehensively examine the influence of gender and gender bias in STEM environments within higher education institutions, and second, to identify potential areas where Computer-Supported Collaborative Learning (CSCL) pedagogical interventions could mitigate these biases among students and teachers in German STEM departments. Employing the innovative group concept mapping method, the research team collaborated with women participants…

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…