The science


Skill Lab:

Science Detective

Carlos M. Díaz

Former Cognitive & Media Psychologist

Skill Lab: Science Detective has three goals. The first goal is to build a community of the ScienceAtHome games’ players by providing them with a fun gaming platform while giving them feedback in the shape of a Cognitive map, which can serve as performance assessment in other games (i.e. commercial off-the-shelf games) or self assessment (i.e. what are your cognitive strengths and weaknesses). The second goal is to create a base of player profiles linked to the other games from ScienceAtHome, allowing better game optimization for future Citizen Science projects. The third goal is to create a database of different cognitive indicators for people with different age, gender, and cultural background, thus allowing drawing perspectives on cognitive normality, cognitive differentiation (e.g. exceptional abilities), and cognitive decline (e.g. dementia. See for example ‘Sea hero quest’ [1]).

Skill Lab: Science Detective aims to explore cognitive skills at different levels, from finely grained skills (such as memory and reaction times[2][3]) to systemic organized high-order cognitive skills (such as Executive functions and Visuospatial reasoning [3][4]). We use the principles of task analysis in human problem-solving [5] for systematically and procedurally evaluate the use of different cognitive skills in problem-solving, how these skills interact, and how they are presented in each of the tasks.

It is not the first time this type of studies are made, for example, the game ‘Sea Hero Quest’ aims to explore and understand dementia based on the analysis of big data of players regarding their spatial navigation skills. Other games such as ‘Crayon Physics Deluxe’ [6] [7] [8] aims for the creation of learning assessment tools for Newtonian physics, seeking not only to assess learning by means of video games but to understand how players and learners generate creative solutions to problems that cannot be tackled by using brute force. Additionally, other authors [9] have explored the use of video games as means of cognitive evaluation batteries for understanding cognitive processes such as spatial and logic reasoning under a processual perspective.

To achieve these goals, Skill Lab: Science Detective is building under the principles of Evidence-centred Design and Stealth Assessment. Evidence-centred Design is a way to collect information which allows us generating inferences about what people know, believe, and do when they are solving a problem in a specific environment[7][8]. Stealth Assessment is a way to invisibly include Evidence-centred Design under the layer of games, so players do not feel evaluated while playing, thus exerting their skills as they will normally do in their everyday life [8].

In addition to this, the motivation that is inherent to the games, as well as some gamification elements, make Skill Lab an engaging tool that can serve multiple purposes in science, from the creation of player profiles for citizen science projects to high-scale assessment of cognitive skills.

Additionally, Skill Lab: Science Detective is built under the principles of neuropsychological [10] and new trends in educational assessment [8], allowing outlining cognitive skills at different levels, including the way different skills interact when doing contextualized tasks.


  1. Glitchers. (2016). Sea hero quest. Retrieved from
  2. Eysenck, M., & Keane, M. (2003). Cognitive Psychology A Student’s Handbook (4th ed.). USA: Psychology Press.
  3. Garnham, A., & Oakhill, J. (1994). Thinking and Reasoning. USA: Basil Blackwell Inc.
  4. Holyoak, K., & Morrison, M. (2005). The Cambridge Handbook of Thinking and Reasoning. USA: Cambridge University Press.
  5. Newell, A., & Simon, H. (1972). Human Problem Solving. USA: Prentice-Hall.
  6. Petri Purho. 2009. Crayon Physics Deluxe.
  7. Shute, V., Moore, G., & Wang, L. (2015). Measuring Problem Solving Skills in Plants vs. Zombies 2. In Proceedings of the 8th International Conference on Educational Data Mining (pp. 428–431). Spain: ERIC.
  8. Shute, V., & Ventura, M. (2013). Stealth Assessment. Measuring and Supporting Learning in Video Games. England: MIT Press.
  9. Castaño, C. & Chavés, L. (2010). ‘Estudio piloto de razonamiento probabilístico, razonamiento silogístico y toma de decisiones por medio de una batería de evaluación procesual (software) en niños entre cinco y nueve años de edad de la ciudad de Medellín’. Thesis to achieve the title of Psychologist. University of Antioquia, Medellín, Colombia.
  10. Luria, A., & Tsvetkova, L. (1990). The Neuropsychological Analysis of Problem Solving. (R. Sbordone, Ed., A. Mikheyev, Trans.). USA: Paul M. Deutsch Press, Inc.
Science Behind Skill Lab: Science Detective