What is the structure of a Challenge Based Learning project? A shortitudinal trajectory analysis of student process behaviours in an interdisciplinary engineering course

Figures & data

Table 1. CBL frameworks with phases and associated process behaviours.

Framework	Phases	Student process behaviours
Apple (Nichols, Cator, and Torres 2016)	1. Engage	Defining the problem Questioning personal interests and the community’s needs Identifying a compelling and actionable challenge statement.
	2. Investigate	Generating and prioritising questions to address the challenge Identifying and using resources or activities to answer the questions Analysing the accumulated data and synthesising it into themes Communicating the proposed solution
	3. Act	Developing solution concepts Developing prototypes, experiments and tests Implementing the solution Measuring outcomes Reflecting on the process Determining the impact on the challenge Refining the solution Communicating the solution
Tec 21 (Gutiérrez-Martínez et al. 2021).	1. Theoretical background	Reviewing and researching the theoretical background
	2. Initial challenge situation	Exploring the challenge situation Defining with the teacher and external stakeholder the objectives, variables, sample size and deadlines for the challenge
	3. Established challenge situation	Understanding, analysing and identifying key elements of the challenge Identifying the process threats and opportunity areas
	4. Guiding activities	Setting a roadmap to address the challenge
	5. Proposed solutions	Generating and analysing proposed solutions
	6. Implementation	Implementing the solution
	7. Conclusion	Evaluating the solution
	8. Continuous improvement	Synthesising findings Communicating findings to the external stakeholder Reflecting on the process
ECIU Challenge-based Learning Framework (Ambrosi and Hermsen 2023) and the CBL ECIU Teamcher Toolkit (Imanbayeva 2021).	1. Engage: Big Idea & Essential Questions	Phrasing essential questions Identifying stakeholders
	2. Engage: Actionable Challenge	Articulating a challenge statement Developing an action plan Identifying personal tasks and roles
	3. Engage: Finalising Actionable Challenge	Asking feedback from the external stakeholder Refining and finalising the challenge definition Setting personal learning objectives
	4. Investigate: Guiding Questions, Activities and Resources	Researching resources, methods and tools related to the challenge Asking stakeholders questions about the challenge
	5. Investigate: Synthesis	Analysing the accumulated data and synthesising it into themes Communicating findings
	6. Act: Solution Concepts and Development	Engaging in design thinking Defining solution requirements Brainstorming possible solutions and solution designs Evaluating different solutions Choosing a final solution Communicating the solution
	7. Act: Solution Implementation	Implementing the solution
	8. Act: Evaluation and sharing	Evaluating the results Deriving conclusions from the process and from the content Communicating the results
STAR Legacy Cycle (Cordray, Harris, and Klein 2009).	1. Challenge Scenario	Discerning which information or activities are relevant to the task
	2. Generate ideas	Eliciting prior knowledge in connection to the challenge
	3. Multiple perspectives	Accessing resources and experts to obtain knowledge Asking questions
	4. Research and revise	Doing field and lab/in-class tests Researching the challenge
	5. Test your mettle	Self-assessing research Self-evaluating learning needs Overcoming misconceptions and gaps in knowledge
	6. Go public	Communicating the solution

Table 2. Real-life interdisciplinary project areas for the CBL course E3Challenge2.

Challenge	Description
Smart mobility	A student team that is part of a European large-scale pilot project investigating the value and potential benefits of adding autonomous vehicles to a worldwide 5G network. The team works on enabling the control of a car from a remote station using an internet connection and feedback from various sensors on the car. Some of the car’s sensors that are necessary for autonomous control cease working and a user must take control of the car from a remote location.
Smart health	The project is a collaboration between the university, a medical centre and a company. It applies the sciences of data learning and biomedical simulations to an existing diabetes gaming platform. The collaboration aims to develop a data-driven, personalised serious game that empowers individuals with diabetes to manage their disease.
Smart energy	The student team collaborates with the university on providing insights into how the campus can be more sustainable. The team aims to develop a model to simulate the main campus buildings, which will allow users to add and configure various technologies such as solar panels, wind turbines, and charging points.

Table 3. Course organisation of an interdisciplinary CBL course in ethics and data analytics.

Course activity	Role	Members of the course team
weekly 2-hour ethics sessions	Delivering ethical content via lectures Practicing ethical reflection on topics relevant to the case and assignments	Ethics lecturer
weekly 1-hour support sessions	Assisting groups in the development of the project and giving process feedback	Teaching Assistants in data analytics and ethics
weekly 30-minute coaching sessions	Discussing weekly reflections on group progress and processes for developing the project Delivering process-related feedback and guidance for individual or groupwork	Coaches (including the course coordinator and the data analytics lecturer)
weekly 1-hour expert meetings	Answering questions and giving expert feedback on technical and ethical aspects related to the project	Technical, ethics, educational experts and sometimes clients
three client meetings	Meeting 1 (week 1): introducing the case Meeting 2 (mid-course): delivering feedback on the tentative solution plan Meeting 3 (week 9): Reacting to and evaluating the solution implemented	Stakeholders Lecturers Coaches (including the course coordinator) Teaching Assistants
two weekly 1-hour peer-to-peer reflective meetings for the teaching team	Meeting a: supporting and guiding the work of teaching assistants Meeting b: discussing notable aspects or challenges occurring during the week and planning ahead	Meeting a: coaches, ethics lecturer, teaching assistants Meeting b: lecturer, experts, coaches, researchers

Table 4. Protocol for shortitudinal qualitative data collection.

Collection method	Focus of data collection	Data description	Collection timelag
Reflections	Process behaviours	How is project progress described or discussed What individual and group processes are mentioned What strategies are mentioned to overcome challenges or make progress	Once weekly, for 10 weeks
	Process experiences	What individual and group challenges are mentioned What individual and group feelings are mentioned What learning experiences are mentioned and what contributed to these
	Temporal markers	When are behaviours and experiences occurring When are past behaviours and experiences described to have occurred
Observations	Verbal process behaviours and interactions	Who speaks to whom How the division of labour is set and what tasks are distributed What and whose suggestions are followed up How is project progress discussed What questions are asked and what are the answers received What feelings are mentioned	Twice weekly (during support sessions and coaching sessions), for 10 weeks
	Physical process behaviours	What people do and who does what Technical behaviours for developing the project Ethics-related behaviours for developing the project
	Process experiences	What challenges and difficulties are mentioned What people’s behaviours may indicate about their emotions
	Temporal markers	When are behaviours and experiences occurring When are past behaviours and experiences described to have occurred
Interviews	Process behaviours	What technical behaviours for developing the project are mentioned What ethics-related behaviours for developing the project are mentioned How is the step-by-step process fordeveloping the project described What project values and stakeholders are mentioned How is the integration of ethics and technical aspects described How the process for deciding the solution is described Mentions of changes in project development	Once, after the end of the course
	Process experiences	What were the most difficult aspects when developing project How was the experience working on a real-life project How was ethics experienced for the project How important was ethics and when did awareness of the importance of ethics occur Ethics issues identified during the process How was the interaction with the client perceived and the helpfulness of their feedback What resources or external support were used to develop the project
	Personal views	Satisfaction with the project developed What course sessions and support were the most useful Views about the role of ethics in engineering now and at the beginning of the course
	Temporal markers	When are behaviours and experiences described to have occurred

Table 5. Coding examples of process behaviours.

Code	Definition	Usage	Exclusion	Example	Occurrence
Evaluating tests for ethical faults	Process behaviour referring to students’ ethical evaluation of tests.	When students evaluate the tests for ethical faults.	When students mention an evaluation of the tests that doesn’t consider ethics.	‘For the test, we would first start with a base solution, like a data-based solution and then we would evaluate that solution to see what potential ethical breaches could be’.	The week when students evaluated the tests for ethical faults or mentioned evaluating tests for ethical faults.
		When students mention that or how they evaluated the tests for ethical faults.	When students mention an ethical evaluation of the final solution
Agreeing on the deliverable	Process behaviour referring to students agreeing on a deliverable.	When students express agreement on the deliverable to be pursued.	When students discuss potential deliverables, without agreeing on one.	‘We were pretty much straightforward and we were all agreeing on the deliverable. There wasn't any discussion because we said the same and that was it’.	The week when students agreed on a deliverable.
			When students agree on other outputs (i.e. subdeliverables, process tasks a.o.).

Figure 1. Occuring CBL process behaviours for each project phase (generated with Atlas.ti).

Figure 2. Temporal occurrence of CBL project phases (generated with Atlas.ti).

Figure 3. Occurrence of group process behaviours (n = 6 groups) for each project phase and week (generated with Sankeymatic).

Table 6. Overview of participants and data collection methods.

Group/participant	Participant observation	Reflections	Interviews
Group 1
Rohit	V	V	V
Aart	V	V	V
Luc	V
Group 2
Thijs	V	V	V
Jean	V	V	V
Krish	V	V	V
Ceyda	V
Group 3
Amir	V	V	V
Willem	V	V	V
Marinus	V	V	V
Bas	V
Group 4
Mila	V	V	V
Marton	V	V	V
Mihai	V
Group 5
Lukas	V	V	V
Maribel	V	V	V
Nic	V
Gabriel	V
Group 6
Sam	V	V	V
Tess	V	V	V
Bram	V	V	V
Kiran	V

Table 7. CBL project phases and associated process behaviours.

Week	W1	W1-W2-W3	W3-W4	W3-W4-W5	W4-W5-W6	W6-W7-W8	W8-W9-W10
Project phase	CLIENT	PROBLEM	CONTEXT	AIM	PATH	TEST AND EVALUATION	SOLUTION
Project focus	Familiarising with the problem area Obtaining direct info about the client’s activity, technical equipment and profile Asking questions about the project process Discussing course expectations Researching the client	Brainstorming the problem area Brainstorming client needs and risks Discussing deliverable expectations Linking the problem area with real-life issues Linking the problem area with the profile and activity of the client Assigning project roles Familiarising with the data and data analysis	Clarifying deliverable expectations Identifying stakeholders Brainstorming stakeholder needs, values and risks	Narrowing client and stakeholder needs and risks Researching the problem area Identifying ethical issues, dilemmas and conflict of interests and values Agreeing on the deliverable	Prioritising process tasks to meet the aim Assigning specialised process tasks Generating solution paths Researching solution paths Engaging in technical tasks Connecting ethics to technical tasks	Testing solution paths Setting values as evaluation criteria Evaluating tests for ethical faults Revisiting stakeholder risks, values, needs and preferences Addressing ethical issues, dilemmas and conflict of interest Researching, optimising and refining tests Clarifying client needs	Adapting tests to client needs and characteristics Synthesising, structuring and writing up data from tests Integrating ethical and technical aspects into the final solution Justifying the solution in terms of value creation and usefulness Communicating the solution

Figure 4. CBL project phases.

Table 8. Group trajectory by project phase and course week

Week Group	WEEK 1	WEEK 2	WEEK 3	WEEK 4	WEEK 5	WEEK 6	WEEK 7	WEEK 8	WEEK 9	WEEK 10
Group 1	Client	Problem	Context	Context	Aim	Path	Testing & Evaluation	Testing & Evaluation	Solution	Solution
Group 2	Client	Problem	Context	Aim	Aim Path	Testing & Evaluation	Testing & Evaluation	Testing & Evaluation Solution	Solution	Solution
Group 3	Client	Problem	Problem	Context	Aim	Path	Testing & Evaluation	Solution	Solution	Solution
Group 4	Client Problem	Problem	Context Aim	Aim Path	Path	Testing & Evaluation	Testing & Evaluation	Testing & Evaluation Solution	Solution	Solution
Group 5	Client	Problem	Context Aim	Aim Path	Path	Testing & Evaluation	Testing & Evaluation	Solution	Solution	Solution
Group 6	Client	Problem	Context	Aim	Path	Path Testing & Evaluation	Testing & Evaluation	Solution	Solution	Solution

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