April 8, 2026
ACA-bot is an engaging chatbot designed for Automated Conversational Assessment (ACA). Drawing inspiration from traditional oral exams, this text-based conversational agent transforms assessment into a dynamic learning experience. It supports both formative and summative evaluation by offering students personalised feedback and guidance at every step of their learning journey. The first ACA-bot prototype focuses on assessing students’ understanding of basic statistical concepts, but its flexible design allows for easy adaptation to a wide range of subjects and learning contexts. Through interactive dialogue, students can practise explaining ideas clearly under exam-like conditions, apply their knowledge to new and challenging questions, and refine their reasoning as they respond to follow-up prompts. They gain valuable insights into their own understanding, identify areas for improvement, and gradually build confidence for both oral and written assessments. For educators, ACA-bot offers a powerful way to scale oral examinations and enhance formative assessment without increasing workload. It automates parts of the assessment process, provides structured and actionable insights into student performance, and opens the door to more personal, interactive feedback at scale. By combining the strengths of conversational AI and educational assessment, ACA-bot turns evaluation into a collaborative, insightful process. It empowers students to think aloud, reason more effectively, and grow, while giving educators a smarter, more innovative way to understand and support learning. ACA-bot is een slimme en inspirerende chatbot die onderwijs en Artificial Intelligence samenbrengt. Geïnspireerd door het klassieke mondelinge examen tilt deze tekstgebaseerde gespreksagent Automated Conversational Assessment naar een nieuw niveau. Studenten krijgen via natuurlijke gesprekken directe, persoonlijke feedback en begeleiding, waardoor leren en toetsen samenvloeien in één boeiende ervaring. Het prototype van ACA-bot is ontwikkeld om kennis over statistiek te beoordelen, maar dankzij het flexibele ontwerp kan het systeem eenvoudig worden aangepast aan andere vakgebieden en toepassingen. Tijdens interactieve dialogen leren studenten helder uitleg geven, hun kennis toepassen op nieuwe vragen en hun redenering aanscherpen. Ze ontdekken waar hun begrip nog verdiept kan worden en groeien zichtbaar in zelfvertrouwen — waardevolle voorbereiding op zowel mondelinge als schriftelijke examens. Ook voor docenten biedt ACA-bot een slimme oplossing. Het maakt mondelinge toetsing schaalbaar, ondersteunt formatieve beoordeling via gesprek, en vermindert de werkdruk door delen van het beoordelingsproces te automatiseren. Bovendien geeft het gestructureerde inzichten in de voortgang en denkwijze van studenten, waardoor elke dialoog bijdraagt aan beter onderwijs. ACA-bot laat zien hoe Automated Conversational Assessment het leren persoonlijker, interactiever en effectiever maakt. Studenten denken hardop, verkennen hun eigen begrip, en verbeteren met vertrouwen — terwijl docenten op een innovatieve, datagedreven manier inzicht krijgen in hoe kennis werkelijk wordt begrepen.
2023
This collection of the Maker Lab's Lecture Slides and Lecture Announcements (alongside the Lecture Notes and several Assignments files) detail the learning material and activities that prepare students for the open inquiry phases. Specifically, students learn about experimental design and uncertainty analysis, and learn and practice some important programming skills for controlling sensors and processing and analyzing data. For context of how these lectures fit into the course activities, please see the example course schedule (published as a sub-page of the main "Maker Lab: full course materials" page). The Lecture Slides are .PDF files of the Powerpoint slides, while the .TXT documents are pre- or post-lecture announcements posted to the course's digital learning environment. The course runs over 15 teaching weeks, with two 90 minute class sessions per week ("a" and "b"), which explains the naming system of these files, with names that begin with the week number and session letter. Note that many class sessions (especially after the open inquiry phases begin in session 5b) have no lectures or other materials because they are devoted to students' team presentations or individual meetings between teams and instructor. Additionally, lectures 1b and 2a include exercises and discussions using Arduino code files, with the file extensions .INO, which are also included here. NOTE: These uploads are not yet working. Please reach out if you're interested in the files. NOTE: Instructors interested in having the original powerpoint files of the Lecture Slides are encouraged to reach out to me via forrestbradbury ("AT") gmail.com .
Forrest Bradbury
May 8, 2018
In this micro lecture the following items will be explained regarding this lecture: Understanding the potential effect of a third variable, more specifically ''interpretation'' (intervening variable)
Henk van der Kolk
May 8, 2018
In this micro lecture the following items will be explained regarding this lecture: Understanding the potential effect of ‘third’ variables, more specifically “interpretation” (intervening variable)
Henk van der Kolk
May 8, 2018
In this micro lecture the following items will be explained regarding this lecture: Theorizing about potential ‘third’ variables. Introducing the word ‘trivariate’.
Henk van der Kolk
Aki Härmä, Julie Bauer