Don´t believe thy hype. 9 problems with the concept of future skills and 21st century skills

I have written at the end of the last semester a critical review of the concept of future-skills in German (preprint available here, still in review) In Germany, there is a plethora of activism around this concept and many higher education institutions feel the need to react to the hype around these skills. This hype even got stronger when ChatGPT got published and now a similar notion under the umbrella of “AI skills” is pushed into the public discourse. I find it really problematic if we start to assume that with every new methodology, technology or important content-area new models or categories of skills are required and I have summarized 9 problems based on earlier published sythesis of evidence of future skills and 21st-century skills:

  1. Lack of integration and relation between concepts

    There are many similar concepts like 21st century skills, transversal skills, future skills and alike and the differences and similarities of these concepts have not been referenced. Furthermore, the differences between knowledge, skills and competences are neglected in many publications leading to a lack of integrative power of these concepts (Halász & Michel, 2011).

  2. Lack of model for specific future skills

    The specificity and relation between what is called a future skill is unclear and a never-ending list of these skills has been produced. In a recent scoping review Kotsiou, Fajardo-Tovar, Cowhitt, Major and Wegerif (2022) have identified 99 future skill frameworks with 341 skills in total.

  3. Lack of evidence regarding impact on adult outcomes

    According to Pellegrino and Hilton (2012) and Lamb, Maire and Doecke (2017) there is not sufficient evidence that what is coined as a future skill or 21st centurity skills has a positive effect on what authors call “adult outcomes”, namely educational success, job success, job satisfaction or civic engagement.

  4. Lack of measurement approaches for future skills

    Without more complex approaches of measurement, future skills can harly be measured. Geisinger (2016) and Greiff & Kyllonen (2016) recommend the measurement via open and unstructured problems and triangulated data.

  5. (Implicit) Downgrading of knowledge

    By stressing methods like design-thinking and introducing new skill requirements from external sources, the role of knowledge in higher education curricula is downgraded and future skills are often positioned as a second agenda besides the domain-related knowledge building. This can be harmful since there is so much evidence that transfer of knowlegde happens based on the domain expertise of learners. Furthermore, there is research evidence that the downgrading of knowledge is harmful for curricula (Rata, 2012; Young, 2013; Priestley und Sinnema, 2014).

  6. Unclear relation to transfer of learning

    Due to the downgrading of domain knowledge there is an unclear relation to initiatives related to near and far transfer of knowledge (Barnett & Ceci, 2002).

  7. Didactical implications

    In the discourse it is not clear if initiatives for future skills are related to setting new learning objectives, new learning activities or new didactucal approaches. This differentiation is important for the development of new teaching approaches.

  8. Missing prioritization of skills

    The lack of order in existing lists of skills leads to an unclear empirical research basis. Pellegrino & Hilton (2012) argue that research should build on evidence and predictors.

  9. Lack of attention to learning contexts and learning environments

    The discourse often neglects the role of (real-world) learning contexts and new learning environments to work on these complex problems.

For the higher education context, the discourse often neglects that academic education is per se directed at the future since the goal is to educate people to contribute to the creation of knowledge. In the article I further argue that it is harmful for higher education institutions if they act in a “vicious circle” in which new skill models for the future are defined without clear evidence that these skills have an impact on adult outcomes. Furthermore I argue that a focus on learning transfer is a much more promisig and evidence-based course of action.


Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn?: A taxonomy for far transfer. Psychological bulletin, 128(4), 612.

Geisinger, K. F. (2016). 21st century skills: What are they and how do we assess them?. Applied measurement in education, 29(4), 245-249.

Greiff, S., & Kyllonen, P. (2016). Contemporary assessment challenges: The measurement of 21st century skills. Applied Measurement in Education, 29(4), 243-244.

Halász, G., & Michel, A. (2011). Key Competences in Europe: interpretation, policy formulation and implementation. European journal of education, 46(3), 289-306.

Kotsiou, A., Fajardo-Tovar, D. D., Cowhitt, T., Major, L., & Wegerif, R. (2022). A scoping review of Future Skills frameworks. Irish Educational Studies, 41(1), 171-186.

Lamb, S., Maire, Q., & Doecke, E. (2017). Key skills for the 21st century: An evidence-based review. Sydney, New South Wales: NSW Department of Education.

Pelegrino, J. W., & Hilton, M. L. (Eds.) (2012). Education for life and work: Developing transferable knowledge and skills in the 21st century. National Academies Press.

Priestley, M., & Sinnema, C. (2014). Downgraded curriculum? An analysis of knowledge in new curricula in Scotland and New Zealand. Curriculum Journal, 25(1), 50-75.

Rata, E. (2012). The politics of knowledge in education. British Educational Research Journal, 38(1), 103-124.

Young, M. (2013). Overcoming the crisis in curriculum theory: A knowledge-based approach. Journal of curriculum studies, 45(2), 101-118.

Marco Kalz
Marco Kalz
Professor of Educational Technology

My research interests is on open education, pervasive technologies and formative assessment to support (lifelong) learning and knowledge construction.