Find. Try. Understand.

First, you name what you are looking for. Then you experiment, make decisions and observe the result. You are not handed the answer — you reach it in your own way.

Searching is part of learning

Less clicking. More thinking.

With thousands of games, a tree would mean one choice after another. Here, you name what you are looking for, recall related ideas and find your own route.

Why does this work? See the research.

Is this your first visit? Open an explanation of how the page works and the research behind it.

The architecture of this page* is not a claim that doit.science is “the best website”. It draws on principles supported by research: adaptive game-based learning*, an appropriate level of challenge, limiting unnecessary cognitive load*, active learning*, simulations* and long-term user experience*.

Why is there no topic tree?

← Back

With 5,000 games, a tree would mean choosing a branch, then another, and then another. The more choices a person has to process, the longer decision-making takes. Direct search shortens that route: enter your own word and immediately see what is related to it (Hick, 1952; Pirolli and Card, 1999).

When people name what they are looking for themselves, they retrieve concepts instead of clicking passively through a structure. Research shows that retrieving knowledge can support understanding, thoughtful searching can form part of learning, and people also remember where information can be found again. Search therefore provides both orientation and practice — it is not a substitute for understanding (Karpicke and Blunt, 2011; Sparrow, Liu and Wegner, 2011; Rieh et al., 2016).

Why choose a game first?

A game provides a shared environment in which several kinds of subject matter can be explored. Once you open it, you select only the year group, subject and topic you currently need. There is therefore no need to look for a separate copy of the same game in different parts of the website.

Why can one game serve several year groups?

The core of the game stays the same, while its content, questions, explanations and level of challenge adapt to the selected year group, subject and topic. A younger pupil can observe a basic phenomenon; an older pupil can work with a more precise explanation or calculation.

Why is the level adapted?

An appropriate level of challenge helps keep a task manageable while still making it stimulating. Research into adaptive game-based learning* examines how adapting content and difficulty relates to learning and motivation* (Chiotaki, Poulopoulos and Karpouzis, 2023; Sampayo-Vargas et al., 2013).

Why is there less unnecessary navigation*?

The user first makes one clear decision: choosing a game. Further options appear only when they are needed. This arrangement limits elements unrelated to the task at hand and therefore reduces unnecessary cognitive load* (Skulmowski and Xu, 2022).

Why might a first impression not be enough?

An initial assessment and the long-term user experience* are not the same. What a person perceives on first contact can change through repeated use, depending on experience, needs and specific tasks (Karapanos et al., 2009; Kujala et al., 2011; Karahanoğlu and Bakırlıoğlu, 2022).

Why try several games and topics?

One game, one topic or one level cannot reveal everything the website offers. Trying different situations repeatedly allows users to discover which parts best support their learning.

Why try first and read the explanation afterwards?

Active learning* involves pupils in making decisions and working through a task. Digital games* and simulations* can create a safe space for experimentation, observing the result and understanding consequences. Research reviews support the educational use* of active learning, digital games* and simulations*, although outcomes always depend on the specific design of the activity and the way the activity is used (Freeman et al., 2014; Clark, Tanner-Smith and Killingsworth, 2016; Rutten, van Joolingen and van der Veen, 2012).

Glossary

Select the large asterisk beside a term in the article to open its explanation. After reading it, select the large asterisk beside the term in the glossary to return to the exact place you came from.

Page architecture *: The way a page’s sections are organised and the sequence of steps a user follows through the page.
Adaptive game-based learning *: Learning through a game in which the content or difficulty adapts to the selected year group, subject and topic.
Cognitive load *: The amount of information and thinking a person must handle at once. Unnecessary elements can increase it and make concentration more difficult.
Active learning *: Learning in which pupils make decisions, experiment, solve a task and observe the result instead of merely receiving a ready-made explanation.
Simulation *: A simplified model of a real situation or process that allows people to explore safely what happens after different decisions.
Long-term user experience *: How a person perceives and uses a website after repeated use in different situations, rather than only when opening it for the first time.
Motivation *: The reasons and inner drive that lead a person to begin, continue or complete a task.
Navigation *: The buttons, links and steps that allow a user to move between parts of a website.
Digital game *: A game played on a computer, tablet or mobile device in which the user controls what happens and receives feedback on their decisions.
Educational use *: Use in teaching and learning designed to help an activity achieve a specific educational objective.

References

Chiotaki, D., Poulopoulos, V. and Karpouzis, K. (2023) ‘Adaptive game-based learning in education: a systematic review’, Frontiers in Computer Science, 5, 1062350. https://doi.org/10.3389/fcomp.2023.1062350
Sampayo-Vargas, S., Cope, C.J., He, Z. and Byrne, G.J. (2013) ‘The effectiveness of adaptive difficulty adjustments on students‘ motivation and learning in an educational computer game’, Computers & Education, 69, pp. 452–462. https://doi.org/10.1016/j.compedu.2013.07.004
Skulmowski, A. and Xu, K.M. (2022) ‘Understanding Cognitive Load in Digital and Online Learning: a New Perspective on Extraneous Cognitive Load’, Educational Psychology Review, 34, pp. 171–196. https://doi.org/10.1007/s10648-021-09624-7
Freeman, S., Eddy, S.L., McDonough, M., Smith, M.K., Okoroafor, N., Jordt, H. and Wenderoth, M.P. (2014) ‘Active learning increases student performance in science, engineering, and mathematics’, Proceedings of the National Academy of Sciences, 111(23), pp. 8410–8415. https://doi.org/10.1073/pnas.1319030111
Clark, D.B., Tanner-Smith, E.E. and Killingsworth, S.S. (2016) ‘Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis’, Review of Educational Research, 86(1), pp. 79–122. https://doi.org/10.3102/0034654315582065
Rutten, N., van Joolingen, W.R. and van der Veen, J.T. (2012) ‘The learning effects of computer simulations in science education’, Computers & Education, 58(1), pp. 136–153. https://doi.org/10.1016/j.compedu.2011.07.017
Karapanos, E., Zimmerman, J., Forlizzi, J. and Martens, J.B.O.S. (2009) ‘User experience over time: an initial framework’, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 729–738. https://doi.org/10.1145/1518701.1518814
Kujala, S., Roto, V., Väänänen-Vainio-Mattila, K., Karapanos, E. and Sinnelä, A. (2011) ‘UX Curve: A method for evaluating long-term user experience’, Interacting with Computers, 23(5), pp. 473–483. https://doi.org/10.1016/j.intcom.2011.06.005
Karahanoğlu, A. and Bakırlıoğlu, Y. (2022) ‘Evaluation of the usefulness of path of long-term user experience model in design process’, Behaviour & Information Technology, 41(4), pp. 777–795. https://doi.org/10.1080/0144929X.2020.1836256
Hick, W.E. (1952) ‘On the rate of gain of information’, The Quarterly Journal of Experimental Psychology, 4(1), pp. 11–26. https://doi.org/10.1080/17470215208416600
Pirolli, P. and Card, S.K. (1999) ‘Information foraging’, Psychological Review, 106(4), pp. 643–675. https://doi.org/10.1037/0033-295X.106.4.643
Karpicke, J.D. and Blunt, J.R. (2011) ‘Retrieval practice produces more learning than elaborative studying with concept mapping’, Science, 331(6018), pp. 772–775. https://doi.org/10.1126/science.1199327
Sparrow, B., Liu, J. and Wegner, D.M. (2011) ‘Google effects on memory: cognitive consequences of having information at our fingertips’, Science, 333(6043), pp. 776–778. https://doi.org/10.1126/science.1207745
Rieh, S.Y., Collins-Thompson, K., Hansen, P. and Lee, H.-J. (2016) ‘Towards searching as a learning process: a review of current perspectives and future directions’, Journal of Information Science, 42(1), pp. 19–34. https://doi.org/10.1177/0165551515615841

For children

Enter what interests you, find a game and explore the subject matter. Searching, experimenting and remembering the route are all part of learning.

For parents

Children are not simply given a ready-made route. They learn to name what they need, make a choice and explain in their own words what they have discovered.

For teachers

One search opens games across different topics without a long chain of clicks. Choosing a game can be the first step towards a question, an experiment and a discussion.

Primary school