Bachelor thesis

Human Factors

BHF1 - Learning minimally invasive surgery

Supervisor: Marleen Groenier and Martin Schmettow

Simulator training and assessment

Minimal invasive surgery (MIS, keyhole surgery) is one of the most important developments in surgery during the past decade. Research has shown that doctors differ in how fast they acquire the necessary  skills, and the proficiency they reach in the long term. Figure 1 shows three example learning curves. 

Figure 1. Leercurves voor efficiëntie van beweging (MotionEfficiency) voor drie verschillende deelnemers (Part) op een laparoscopie taak (Lifting & Grasping).

These differences can partly be explained by individual differences between doctors, such as amount of training and cognitive capabilities, like visual-spatial processing ability.

In fact, minimally invasive procedures are quite demanding in terms of spatial orientation, as

  • there is no perception of depth
  • the procedure often require counter-intuitive movements
  • haptic feedback is limited

Therefore, a good mental representation of the situation and good eye-hand coordination are crucial.

In the past and present, MIS training followed the apprenticeship model, where trainees watch a hundred or so procedures, before putting their own hands on a patient. With the emerge of virtual reality training simulators this is soon going to change. This new technology is promising as it provides safe and highly repeatable training opportunities.

MIS simulators have even greater potential during the process of training. In every simulator session an abundance of performance variables are recorded (e.g., motion efficiency, see Fig 1). It is compelling to use such data to track the training progress of individual trainees. Furthermore, using learning curves, it may be possible to predict ahead of time, what performance level a trainee is going to reach (for example, participant 06 will reach a much better level than 03). In the future it may be possible to use learning curves from simulator data to select high potentials for a training program.

In your bachelor project you will run a simulator study on novice participants in one of three fields:

  1. laparoscopy deals with diagnosis and surgery in the abdomen
  2. bronchoscopy is the diagnosis and treatment in the lungs
  3. endovascular surgery takes place in the blood vessels, e.g. to treat an angina pectoris

Based on the results you will draw conclusions on the span of individual differences and the feasibility of simulator-based assessment. During your project you will work together in a team consisting of one master student and one or two bachelor students. You will get supervision from Marleen Groenier (Technical Medicine) and Martin Schmettow (Psychology).

BHF2 - The role of trust in technology before the use of a new product

Supervisor: Simone Borsci

* De opdracht en begeleiding is in het Engels

* The assignment and guidance is in English

1.    The role of trust in technology before the use of a new product

Every day people use multiple technologies to perform complex tasks, such as buying products online, informing their decision making, or supporting their work activities. Several independent evidences in literature converge on the idea that multiple elements affected people expectations toward the use of a technology, including individual attitudes, skills and capabilities and technology related aspects, such as: product’s aesthetics and usability perceived before the use, fluency, brand and price etc.

In many cases (high risk) processes are dependent on the technology to deliver the appropriate service. It is perhaps reasonable to assume that the implicit agreement of this technology-driven world is that: people trust technology they are using to perform task and decision making in terms of: performance, functionalities and reliability of outcomes. Trust toward technology does not happen immediately but rather is built throughout the relationship between user and artefacts. This is a set of beliefs about a product’s characteristics – i.e., functioning, reliability, safety, etc. And it results from the gained experience of people in the use of different technologies over time. User’s overall trust is, therefore, strongly related to the concept of user experience, i.e., experience with (and the exposition to) different products enable people to develop a set of general attitudes and beliefs toward those technology, including the overall trust.

The main objectives of this dissertation project are to: i) analyse the current state of art around the concept of trust in different fields, and ii) attempt to identify models about the role of trust in the user experience with digital and physical products.

Small samples of participants will be used to gather data and to test hypotheses in tune with literature. The focus of the work will be on how to assess trust before the use of a new product (digital and/or physical), and how trust affects expectations and experience after the use.

Research questions could be (not limited) for instance to the following: Which are the mechanisms behind trust? How trust can be assessed? Which is the relationship among trust, acceptance, aesthetics and usability?

List of references related to the topic:

Borsci, S., Lawson, G., Salanitri, D., & Jha, B. (2016). When simulated environments make the difference: the effectiveness of different types of training of car service procedures. Virtual Reality, 20(2), 83-99. doi: 10.1007/s10055-016-0286-8

Corbitt, B. J., Thanasankit, T., & Yi, H. (2003). Trust and e-commerce: a study of consumer perceptions. Electronic Commerce Research and Applications, 2(3), 203-215. doi:

Fruhling, A. L., & Lee, S. M. (2006). The influence of user interface usability on rural consumers' trust of e-health services. International Journal of Electronic Healthcare, 2(4), 305-321. doi: 10.1504/ijeh.2006.010424

Gefen, D. (2000). E-commerce: the role of familiarity and trust. Omega, 28(6), 725-737. doi:

Karat, C. M., Brodie, C., Karat, J., Vergo, J., & Alpert, S. R. (2003). Personalizing the user experience on IBM Syst. J., 42(4), 686-701. doi: 10.1147/sj.424.0686

Lankton, N. K., & McKnight, D. H. (2011). What does it mean to trust facebook?: examining technology and interpersonal trust beliefs. SIGMIS Database, 42(2), 32-54. doi: 10.1145/1989098.1989101

Lawson, G., Salanitri, D., & Waterfield, B. (2016). Future directions for the development of virtual reality within an automotive manufacturer. Applied Ergonomics, 53(Part B), 323-330. doi:

Lippert, S. K., & Swiercz, P. M. (2005). Human resource information systems (HRIS) and technology trust. Journal of Information Science, 31(5), 340-353. doi: 10.1177/0165551505055399

Marie Christine, R., Olivier, D., & Benoit, A. A. (2001). The impact of interface usability on trust in Web retailers. Internet Research, 11(5), 388-398. doi: 10.1108/10662240110410165

Mcknight, D. H., Carter, M., Thatcher, J. B., & Clay, P. F. (2011). Trust in a specific technology: An investigation of its components and measures. ACM Trans. Manage. Inf. Syst., 2(2), 1-25. doi: 10.1145/1985347.1985353

Montague, E. N. H., Winchester, W. W., & Kleiner, B. M. (2010). Trust in medical technology by patients and healthcare providers in obstetric work systems. Behaviour & Information Technology, 29(5), 541-554. doi: 10.1080/01449291003752914

Pennington, R., Wilcox, H. D., & Grover, V. (2003). The Role of System Trust in Business-to-Consumer Transactions. Journal of Management Information Systems, 20(3), 197-226. doi: 10.1080/07421222.2003.11045777

Salanitri, D., Hare, C., Borsci, S., Lawson, G., Sharples, S., & Waterfield, B. (2015). Relationship Between Trust and Usability in Virtual Environments: An Ongoing Study. In M. Kurosu (Ed.), Human-Computer Interaction: Design and Evaluation: 17th International Conference, HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015, Proceedings, Part I (pp. 49-59). Cham: Springer International Publishing.

Salanitri, D., Lawson, G., & Waterfield, B. (2016). The Relationship Between Presence and Trust in Virtual Reality. Paper presented at the Proceedings of the European Conference on Cognitive Ergonomics, Nottingham, United Kingdom.

Shin, D.-H. (2013). User experience in social commerce: in friends we trust. Behaviour & Information Technology, 32(1), 52-67. doi: 10.1080/0144929x.2012.692167

Ziefle, M., Rocker, C., & Holzinger, A. (2011, 18-22 July 2011). Medical Technology in Smart Homes: Exploring the User's Perspective on Privacy, Intimacy and Trust. Paper presented at the 2011 IEEE 35th Annual Computer Software and Applications Conference Workshops.

BHF3 - Evaluation methods to support the development of usable chatbot

Supervisor simone borsci

* De opdracht en begeleiding is in het Engels

* The assignment and guidance is in English

2.    Evaluation methods to support the development of usable chatbot

Chatbot, intended as computer programs designed to simulate the conversational interaction with people, are increasingly used in the human interaction with digital and online service.

Usability and perceived usefulness of this type of technology play an important role in shaping the end-user experience with a service and the success of the online problem-solving strategies. Standardised approaches to evaluate the Human-Chatbot Interaction are currently missing.

The main objectives of this dissertation project are to: i) review the state-of-art on the quality of interaction assessment with chatbot tools, ii) test and gather initial data to evaluate this emerging type of interaction, and iii) to identify a toolkit of methods and reliable tools which may be adapted and used to support future research on chatbot.

Small samples of participants will be used to gather experimental data and test hypotheses in tune with literature.

Research questions could be (not limited) for instance to the following: How to measure efficiency, effectiveness and satisfaction in the context of chatbot interaction? Which is the relationship among usability and end-user perceived usefulness of a chatbox tool?

List of references related to the topic:

Coperich, K., Cudney, E.,& Nembhard, H. Continuous Improvement Study of Chatbot Technologies using a Human Factors Methodology.

Duijst, D. (2017). Can we Improve the User Experience of Chatbots with Personalisation? MSc Information Studie, Amsterdam.  

Følstad, A., & Brandtzæg, P. B. (2017). Chatbots and the new world of HCI. interactions, 24(4), 38-42.

Hill, J., Ford, W. R.,& Farreras, I. G. (2015). Real conversations with artificial intelligence: A comparison between human–human online conversations and human–chatbot conversations. Computers in Human Behavior, 49, 245-250.

Kuligowska, K. (2015). Commercial Chatbot: Performance Evaluation, Usability Metrics and Quality Standards of Embodied Conversational Agents. Browser Download This Paper.

Xuetao, M., Bouchet, F.,& Sansonnet, J.-P. (2009). Impact of agent’s answers variability on its believability and human-likeness and consequent chatbot improvements. Paper presented at the Proc. of AISB.