CPEGraduationBachelor thesisCognitive Psychology

Cognitive Psychology

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  • BCP1 - Is motor learning better with backward than with forward chaining? (3 students)


    Backward chaining is a method to improve the effect of practice. It entails practicing first later parts of a serial movement pattern and then the earlier parts are added. Forward chaining involves practicing first the earlier part and only then the later part is included in practice.

    The two projects will test the hypothesis that backward chaining improves learning more than forward chaining, and that this holds especially with limited practice while this learning difference will be reduced with extended practice. These hypotheses will be tested in two related bachelor projects in BMS lab. Each involves an experiment in which participants will develop automaticity by practicing two fixed movement patterns while reaction times and error are measured. The results will contribute to guidelines how the development of sequential motor skills can be optimized.

    Abrahamse, E. L., Ruitenberg, M. F. L., De Kleine, E., & Verwey, W. B. (2013). Control of automated behaviour: Insights from the Discrete Sequence Production task. Frontiers in Human Neuroscience, 7(82), 1-16.

    Fontana, F. E., Mazzardo, O., Furtado Jr, O., & Gallagher, J. D. (2009). Whole and part practice: A meta-analysis. Perceptual and Motor Skills, 109(2), 517-530.

    Wightman, D. C., & Lintern, G. (1985). Part-task training for tracking and manual control. Human Factors, 27(3), 179-209.

  • BCP2 - Short-Term Memory for Color, Form or Orientation (1 student)


    Recent ideas on working memory or short-term memory (STM) propose that STM may be better conceptualized as a limited resource that is flexibly distributed among items to be maintained in memory rather than holding a fixed number of elements active. Many aspects of STM are still unknown. In this project, we will especially focus on memory for colors/form/orientation. How precise are our memories for color/form/orientation and how does this preciseness depend on the number of presented objects? (Requirement: ability to program your experiment in Python)

  • BCP3 - Short-Term Memory and Ageing (1 student)


    Working memory or short-term memory (STM) seems to decline as a function of ageing. A recent BA project revealed that effects of aging on the preciseness of our memories may already be present for the middle-aged. Goal of the project is to examine this decline in more detail in the current project by improving on the previous project.  (Requirement: ability to program your experiment in Python)

  • BCP4 - Testing the Motor-Cognitive Model of Motor Imagery (1 student)


    A dominant view in the field of motor imagery is the functional equivalence model (Jeannerod, 2006). This model implies that the processes activated during motor imagery are the same as the processes activated during motor execution, except for the execution itself. Recently, it has been proposed that in case of complex new movements additional processes are activated as motor imagery requires more control and possibly inhibition: the motor-cognitive model. Goal of the project is to examine at what level of response complexity the motor-cognitive model provides a better explanation for performance than the functional equivalence model. This will be done by comparing the durations of physical and mental execution of motor tasks that vary in complexity. (Requirement: ability to program your experiment in Python)

  • BCP5 - Progressing Chunking For Motor Enhancement (1 student)


    The enhancement of motor learning is an important aspect of gaining expertise.  When learning becomes an automated process, it is assumed that motor chunking is the main modality that is used to perform fast and accurate movements (Verwey & Abrahamse, 2012; Verwey et al., 2015).  Yet across many learning paradigms, training remains fixed.  One of the most important dichotomy in the literature is the use of Part versus Whole practice (Naylor & Briggs, 1963; Schmidt & Wrisberg, 2008).  The goal of this experiment is to understand if breaking down a complex motor sequence can have benefits compared to just practicing as a whole.  As a bachelor student, you will recruit participants and use a dance-step discrete sequence performance task to investigate whether using smaller chunks will facilitate better learning than practicing the whole sequence. You will have a chance to work closely with the main supervisor to apply R and build statistical models to investigate these differences using mixed-effects models.  You may also have the opportunity learn and assist with neuro data collection in the form of fNIRs.

    Requirement: 1 student with statistical understanding, interested to learn R and/or Python.


    Verwey, W. B., & Abrahamse, E. L. (2012, Jul). Distinct modes of executing movement sequences: reacting, associating, and chunking. Acta Psychol (Amst), 140(3), 274-282. https://doi.org/10.1016/j.actpsy.2012.05.007              

    Verwey, W. B., Shea, C. H., & Wright, D. L. (2015, Feb). A cognitive framework for explaining serial processing and sequence execution strategies. Psychon Bull Rev, 22(1), 54-77. https://doi.org/10.3758/s13423-014-0773-4       

    Naylor, J. C., & Briggs, G. E. (1963). Effects of task complexity and task organization on the relative efficiency of part and whole training methods. J Exp Psychol, 65(3), 217-224. https://doi.org/10.1037/h0041060

    Schmidt, R. A., & Wrisberg, C. A. (2008). Motor learning and performance: a problem-based learning approach. (4th ed.). Human Kinetics.

  • BCP6 - Mental Training For Cognitive Enhancement In Motor Learning (2 students)


    Cognitive enhancement is quickly becoming a buzzword across in the world of sports and motor training.  Particularly meditation is one of the fastest growing method in which it is believed to give athletes an edge during performance (Chan et al., 2018; Immink, 2016).  One style known as open monitoring meditation (OMM) would elicit the use of more creative solutions to motor learning (Immink et al., 2017).  The goal of this experiment is to understand if learners that use OMM prior to motor learning will gain enhanced learning outcomes compared to learners not exposed to OMM.  You will be using the dance-step discrete sequence performance task to measure motor learning alongside with measurements arousal and affect.  You will have a chance to work closely with the main supervisor to apply R and build statistical models to investigate these differences using mixed-effects models.  You may also have the opportunity learn and assist with neuro data collection in the form of fNIRs.

    Requirement: 2 student with statistical understanding, interested to learn R and/or Python.


    Chan, R. W., Lushington, K., & Immink, M. A. (2018). States of focused attention and sequential action: A comparison of single session meditation and computerised attention task influences on top-down control during sequence learning. Acta Psychol (Amst), 191, 87-100. https://doi.org/10.1016/j.actpsy.2018.09.003

    Immink, M. A. (2016). Post-training Meditation Promotes Motor Memory Consolidation [Original Research]. Front Psychol, 7(1698). https://doi.org/10.3389/fpsyg.2016.01698

    Immink, M. A., Colzato, L. S., Stolte, M., & Hommel, B. (2017). Sequence Learning Enhancement Following Single-Session Meditation Is Dependent on Metacontrol Mode and Experienced Effort [journal article]. Journal of Cognitive Enhancement, 1(2), 127-140. https://doi.org/10.1007/s41465-017-0019-2

  • BCP7 - Do you see what she means? Evaluation of creative associations (2 BA students)


    Creative thinking has recently sparked considerable interest among scholars in areas such as psychology, communication, or marketing.  How people create novel ideas and how these are understood by others is at the core of this interest. In a previous study a pool of creative word associations was collected from a group of participants who completed the task in the laboratory. They were given a word, e.g., beach and created novel associations with these words, e.g., frying pan. They also provided explanations of their associations, for our example it could be as follows: people lying on the beach can get sunburn like food can get burnt on the frying pan. In this BA project, we will collect data from another group of participants who will evaluate whether the associations created by the first study participants are indeed creative. In the final step, we will compare these evaluations to other measures of creativity, e.g., semantic vectors. The semantic vectors and the data from the first study will be provided to you, and your main task will be to (1) conduct a rating scale study and (2) test whether the evaluations are associated with other measures of creativity.

  • BCP8 - What features of a face are responsible for the Uncanny Valley effect? (3 students)

    It is expected that robots will soon appear in the areas of senior and health care, where they support staff (e.g., lifting of patients) and act as social companions (e.g., for elderly and handicapped persons). But people are sometimes skeptical towards technology, especially when they don’t understand it. So, an important condition of success is that robots are designed to induce trust.

    It is commonly assumed, that making a social robot more human-like in appearance and behavior will improve acceptance and trust. However, there is a limit to this approach, which is called the Uncanny Valley. The Uncanny valley effect arises as s sudden drop in the emotional response when a robot face reaches a certain resemblance with a human face, the emotional response takes a sudden drop, hence the valley. The cognitive mechanisms behind this strange phenomenon are currently unclear. Mathur & Reichling (2016) provide evidence that the Uncanny Valley exists in robot face perception. In a number of own studies, we have shown that the Uncanny Valley effect is rooted in early visual processing and is practically universal, i.e. there aren’t any individual differences.

    For the clarification of underlying cognitive mechanisms, it is crucial to understand what features of a face are responsible for the effect. For this purpose, you will design and run an Uncanny Valley experiment using eye tracking.

    Activities during the project:

    1. Review the literature on the Uncanny Valley effect, face perception and evolutionary psychology
    2. Specify the research questions
    3. Collect a set of stimuli
    4. Develop an eye tracking experiment in Python
    5. Collect and analyze the results
    6. Discuss your results regarding possible explanations for the Uncanny Valley effect


    This project is intended for a team of three students. Prerequisites are good command of Python and R. Interested? Ask Martin Schmettow (m.schmettow@utwente.nl)

    Mathur, M. B., & Reichling, D. B. (2016). Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley. Cognition, 146, 22–32. https://doi.org/10.1016/j.cognition.2015.09.008

    Koopman, R. (2019, January). The Uncanny Valley as a universal experience : a replication study using multilevel modelling. Retrieved from http://essay.utwente.nl/77172/

    Geue, L. (2021, July). From Robots to Primates : Tracing the Uncanny Valley Effect to its Evolutionary Origin. Retrieved from http://essay.utwente.nl/87564/