Evaluation 3.0: Are we evaluating computational thinking?

Evaluation, exam, test... all these words evoke a feeling of fear and dread in us. But this shouldn’t be the case. With a bit of luck and a lot of hard work, future generations will not have to face school evaluations in the same way we did. Because, just as we no longer travel by wagon or light our homes by candlelight, we can no longer evaluate our students in the same way as we did 100 years ago. Here we offer some guidelines on how to evaluate computational thinking learning in the light of new trends in evaluation.

Evaluation 3.0: Are we evaluating computational thinking?

We know that the evaluation of learning is one of the most important elements of the educational process. Evaluation (a good evaluation) must go beyond the mere verification of the acquisition of knowledge. It must be the driving force of the learning itself: an instrument to be used by teachers and learners, enabling them to build and take ownership of the educational process. What to learn and how to learn it.

It’s true that, over the last few years, the world of education has been progressively changing to adapt to modern day society. Thus, we see how teaching methodologies are changing and becoming much more active and relevant to the learner; how the learner is becoming the centre of education; and how educational resources have been turned upside down by new information and communication technologies. However, evaluation practices still remain rather traditional and not very permeable to the innovations that are taking place in the field of education. The inevitable question, then, is how should new ways of teaching and learning be evaluated in the digital age? What should we measure? How can we ensure that evaluation becomes the formative instrument that it should be and from which we learn as much or more than we do in the other stages of the training process?

The specialised blog, Revoluación, offers us some tips to promote learning from evaluation; it is therefore essential that it is a transparent and participatory process at all times. This means that, prior to the evaluation, learners should understand what the learning goals are, what kind of evaluation will be used to assess whether those goals have been achieved and what criteria will be used to assess their work; and afterwards, they should be given clear feedback on how they have done and what they can do on future occasions in order to improve. The teacher can also learn from the evaluation by analysing it and studying the results to detect possible failures and find out what each student’s strengths and weaknesses are.

Taking all these factors into account, how can we approach evaluation in a pedagogical proposal using computational thinking? What do we measure? What instruments and strategies should we use? How can we carry out a formative evaluation? Evaluation strategies for computational thinking in education is an area of knowledge that is still needs further development. However, based on ProFuturo’s experience, we have extracted some guidelines on how to properly evaluate this new educational proposal that is becoming increasingly present in education systems around the world.

  1. Pre-evaluation: the degree of teachers’ expertise and the infrastructure of schools varies greatly depending on various factors. It is therefore highly recommended to carry out an initial self-diagnosis to help teachers to choose the learning experiences that best suit their educational context, depending on the age of their students, their teaching style, the resources available, etc.
  2. Clear, simple and measurable evaluation of competencies: each of the experiences carried out must include well-defined processes and competencies; and these, in turn, must be associated with a series of criteria and achievement indicators. In this way, it is possible to evaluate whether they have been achieved using a clear and simple reference.
  3. Rubrics: it is also advisable for the final product corresponding to each experience to have a rubric that helps both students and teachers to evaluate it. This rubric should be available throughout the process of creating the final product, so that it serves as a continuous reference.
  4. Metacognition: computational thinking is particularly suited to developing metacognition, i.e., knowledge about one’s own cognitive processes (a very useful skill for all aspects of life). In order to encourage the development of metacognition, in each experience, it is advisable to incorporate questionnaires that help the student to analyse and be aware of the metacognition processes involved in the said experience.
  5. Evaluating the experience itself: designing questionnaires to gather information on learner satisfaction in relation to each learning experience will help us to improve these experiences. This will enable us to make improvements to the itineraries in the future.

These are just a few ideas based on a specific experience, but they can and must be enriched through contributions from all those involved. Computational thinking has been in the spotlight for some years now, but the same cannot be said for its evaluation processes. It is time to open the debate.


Cabrera Rodríguez, F. (2020). Si no cambiamos nuestra lógica evaluativa poco cambiaremos en Educación. Asociación Educación Abierta. https://educacionabierta.org/si-no-cambiamos-nuestra-logica-evaluativa-poco-cambiaremos-en-educacion/

Cortés de las Heras, J. (23 September 2017). Tres pasos para promover el aprendizaje desde su evaluación. Revoluación. http://revoluacion.blogspot.com/2017/09/tres-pasos-para-promover-el-aprendizaje.html


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