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HBO/WO

MBO

2023

Maker Lab resource list: facilities/equipment/software

For now, there is no document to share beyond this summary of the facilities, equipment, and software: FACILITIES: The Maker Lab is a fully flipped lab in the sense that students mainly do their experimental work outside of the classroom without teacher supervision. Thus, no laboratory is needed. The class-sessions happen in a regular classroom. The only lab-related "facility" is a 4 square meter closet (the "Maker Closet") where the the equipment is stored: EQUIPMENT: each pair of students gets toolboxes to take home which all contain Arduinos, pliers, wires, breadboards, etc. The "Maker Closet" additionally stores various electronic sensors and basic electronic and construction tools and supplies (connectors, tape, tripod-stands, batteries, SDcards, etc). Note: Fairly often, students identify useful sensors (or supplies) that are not stocked but are affordable and well-suited to their research plans. Suppliers of Maker tools and electronics often have great user manuals and instructional videos and can ship these products quickly. Students submit receipts and are reimbursed for their purchases, which in turn helps to grow the collection of equipment each year. SOFTWARE: students need the following free software: Arduino IDE software (Interactive Development Environment) the Python Anaconda distribution, which includes Jupyter Notebook sometimes also drivers for interfacing their laptops with the Arduino via a USB cable

Forrest Bradbury

2023

Maker Lab: full course materials

This is an open inquiry natural science lab course utilizing Maker tools (e.g. inexpensive electronic sensors/sensorboards controlled by Arduinos). Students are tasked with conceiving, designing, and carrying out scientific experiments with significant process guidance but little experimental oversight, instead leveraging the Maker movement's online resources and open source hardware and software tools. Target audience: The course is given at Amsterdam University College to a multidisciplinary mix of natural science bachelor's students, usually in their second or third year of a three year bachelor's. Duration / Study load: 6 ECTS course, equivalent to ~168 total hours of student work, evenly spread across a 16 week term Over-arching learning goals: (see also the Learning Objectives subpage for specific, assessable list) students navigate the iterative empirical research process, including conception, experimental design, testing, data & uncertainty analyses, and drawing conclusions students build self-efficacy in conducting quantitative empirical research and creating scientific knowledge students improve science communication skills in an authentic (team) setting Directory: Course materials are published in the following locations (see links to them below) course description (pre-requisites, learning activities, teaching roles, grouping of students, learning environment) learning objectives course schedule readings and lecture slides for students assignments (and rubrics) resource list: facilities, equipment, software JupyterPython-materials zip file This page's linked websites give official course descriptions. Any questions about this Maker Lab course can be addressed to Forrest via: forrestbradbury@gmail.com

Website

Forrest Bradbury

2023

Maker Lab Assignments: Two Main Open Inquiry Projects

Two thirds of the Maker Lab course is dedicated to two large open inquiry projects which students conceive, design, and carry out in pairs. As detailed in Appendix 1 of the Maker Lab course description (linked below), there are seven rules limiting students' open inquiry project topics: projects must involve empirical research in one or more of the natural sciences the research methods must utilize quantitative modeling of empirical measurements the research methods must utilize an Arduino in some non-trivial way (usually for controlling electronic sensors, or sometimes just using its voltage measurement capabilities) something in the inquiry must go beyond high school level science: the research methods (measurement techniques and/or mathematical modeling) and/or the scientific phenomena being studied projects must be doable within the allowed time, with some buffer for inevitable failed trials or delays and time to iteratively improve • no more than 40 euros may be spent per project (often for buying a new kind of sensor or various unstocked equipment or supplies). Basic supplies are already included in the student toolboxes and many other types of equipment are already in-stock in the Maker Closet, so permission must be asked and granted before purchasing items. The costs (including shipping) will be reimbursed if reusable equipment will be returned (or if consumable items are used sparingly) and if official receipts of purchases are submitted. Finally, since the projects are relatively short, shipping times need to be a couple days max and shipping from outside the EU is not possible (due to long delays in customs). students must follow safe and ethical practices in their work, where safety is regulated by adhering to equipment user manuals and discussions with instructor (and direct supervision and/or help if dangerous equipment or substances are required), while ethical practices begin by following AUC’s ethics checklist and oversight procedures for pursuing any experiments with humans, animals, data or property of others, or environmental systems. See Canvas for more information. The subpages below link to the following: grading form for pre-recorded video "Midway" presentation grading form for pre-recorded video "Final" presentation Maker Lab course schedule (example) where the open inquiry supervision process is detailed per class-session Maker Lab course description, which includes practicalities of the open inquiry process and assessment Lecture Notes chapter 6: Empirical Research Process (a rough guide to the iterative process of empirical open inquiry) Additionally, this page itself includes two documents: a template for the students' pre-proposal at the start of each open inquiry project (which must be approved by the instructor) a template for students' electronic lab journals (which is not currently assessed for the course grade) Both of these template documents are Jupyter Notebook files. If you do not (yet) have Jupyter Notebook, you cannot fully utilize the .ipynb file. But the PDF documents (also attached) will give an idea of their content and functionality.

Forrest Bradbury

2023

Maker Lab course description

This Maker Lab course description is an internal document which communicates the structure of the course to students. Some extra comments are also included for the benefit of interested instructors.

Document

Forrest Bradbury

2023

Maker Lab course schedule (example)

This example Maker Lab course schedule is meant to help show how the course is structured and implemented. In addition to the full .pdf schedule, a pictoral representation is given to show the basic timeline, starting with skills training and then two open inquiries. Note that this example schedule has benefitted from four previous course iterations, and has been tweaked each time for better and more efficient student support. Instructors implementing open inquiry lab projects for the first time are advised to schedule in a bit extra student contact time until they have a good sense of when and how the students need to be supported.

Afbeelding

Forrest Bradbury

2023

Maker Lab Assignment: Semi-structured_Experiments

Before the Maker Lab students begin the open inquiry phases, they first learn and practice some important skills, supported by small assignments. This assignment is a "structured", or "guided" inquiry, where students know ahead of time the result they should find, but have agency in their experimental design, within some prescribed limits. By assigning all teams different methods for addressing a single research question (currently: estimating the acceleration due to gravity), they are encouraged to reflect upon how experimental design and equipment limits the certainty of empirical findings. This assignment requires teams of four students (organized into two pairs, each performing the experiment separately, but analyzing data and reporting on conclusions together). In two weeks (wherein students' course workload is 10 hours per week), the teams must set up experiments, controlling sensors with self-programmed Arduinos, collect and analyze experimental data, and create a pre-recorded video presentation to be viewed in class and aimed at their peers, followed by a Q&A. Note: If you do not (yet) have Jupyter Notebook, you cannot fully utilize the .ipynb file. But the attached PDF will give an idea of its content and functionality. Note also: In order to interact with and fully utilize the Jupyter Notebook documents (including their hyperlinks and pointers to data and image files), it is helpful to save the entire collection locally in a way that preserves the original directory structure. This is easiest to accomplish by downloading all files at once via the JupyterPython-materials zip file and unpacking it (extracting the files) to your preferred local directory. This zip file of all Jupyter Notebook materials is located here: https://search.edusources.nl/materialen/d144774e-9705-489a-b3cd-28e3618f7324 Contents: partial experimental instructions (for students) in Jupyter Notebook: Semi-structured_Experiments.ipynb (and .pdf ) grading form for pre-recorded video presentation (both .docx and .pdf )

Document

Forrest Bradbury

2020

Resource list Molecular Neurobiology

The resources used for Molecular Biology are: Facilities: Practical rooms for labwork Practical rooms for cell culture Lecture halls Rooms for labmeetings Necessities: Protocols (see attached learning material (Reader Molecular Neurobiology)) Equipment and consumables (attached file) Software LabBuddy and ExperD as online reader and experiment designer (see link)

Spreadsheet

Simone Mesman

2023

Maker Lab Lecture Slides and Lecture Announcements

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 .

Document

Forrest Bradbury

2023

Maker Lab Open Inquiry: Presentation grading forms

Each of the Maker Lab's two Open Inquiry projects requires two graded presentations: a midway presentation by one of the two team members, and a final presentation by the other team member. These are submitted as pre-recorded videos. The midway videos are played during class, each followed by 10 minute live-Q&A sessions with peers and instructor(s). The final videos, on the other hand, are not played during class. Instead the presenter gives an abbreviated live version during class, followed by a 5-10 minute live-Q&A session with peers and instructor(s). Students are instructed to pitch the level of the talk at their peers (who have not done nor closely followed their inquiry). Students are further given these grading forms in advance to see on which assessment criteria their talk will be judged. Note: Simple "grading forms" are used instead of rubrics, with the difference being that performance levels are not individually described. I use grading forms instead of rubrics for several reasons: 1. I am the only grader for the course, thus inter-rater reliability is not an issue. 2. I include 10-12 specific assessment criteria which themselves help to communicate expectations, 3. The diverse student projects make it difficult to create meaningful level descriptors, and 4. I often leave explanatory remarks under the individual assessment criteria to explain my marks.

Document

Forrest Bradbury

19 maart 2026

ShareXR : Challenge-Based Learning with XR (BMS Lab, University of Twente)

ShareXR introduces a challenge-based learning (CBL) approach for integrating research, design, and development in engineering education through extended reality (XR). Developed at the University of Twente’s BMS Lab, the model addresses the increasing need for multidisciplinary collaboration by teaching students to speak a shared language across research, design, and technical development. Even for those without an engineering, scientific or STEM background. This course offers a hands-on, multidisciplinary learning experience where students take real research ideas and transform them into innovation projects within a complete and validated open learning XR ecosystem. With reusable multimedia course content, the course enables students to understand interdisciplinary collaboration, while each module focuses on one of the four pillars: Research, Design, Development, and Project Management — guided by principles of balance, iteration, and collaboration. By working with different tools like one-page project canvases, students will learn how to translate research ideas into structured user stories, requirements, and project management tasks, while exploring how XR tools can act as a human-centered medium for prototyping, testing, and validating ideas without requiring coding skills.

App

Lucia M Rabago Mayer, Jordi Weldink, Amanda Poulin, Luca Frösler, Peter Slijkhuis, Mirjam Galetzka, Benno Pals, Jan-Willem van 't Klooster