Investigation of Teacher Candidates’ 21st Century Learner Skills via PAMS

Tuncer Akbay, Sadık Yüksel Sıvacı, Lokman Akbay


In this study we aim to examine the latent profiles of teacher candidates’ 21st century learner skills. In other words, we intend to discover the profiles of participant groups who hang together in terms of 21st century learner skill scores. The data are gathered from students who enrolled in either undergraduate programs in the school of education or pedagogical formation certificate programs. For data collection purposes, we used the 21st century learner skills usage inventory. In order to achieve our goal, profile analysis via multidimensional scaling approach is employed. Data analysis resulted in two-dimensional solution indicating two major profile patterns. Students whose observed patterns are similar to the first major profile tend to have lower ability in cognitive processing and coding of information and realization of the products. They tend to have higher abilities in self-management, self-control, designing more flexible learning environment, and adaptation of new technology. These students are expected to be better at collaboration-based activities. Students whose observed patterns are similar to the second major profile are expected to be good at self-management, self-control and they are expected to have higher self- and collaborative-learning abilities.


Multidimensional scaling, Profile analysis, PAMS, The 21st century learner skills.

Full Text:



American Association of School Librarians. (2007). Standards for the 21st century learner. Retrieved from:

Ananiadou, K., & Claro, M. (2009). 21st century skills and competences for new millennium learners in OECD countries. 21 August 2019 Retrieved from:

Bulut, O., & Desjardins, C. D. (2016). profileR: Profile analysis of multivariate data in R (R package version 0.3, URL

Davison, M. L., Kim, S. K., & Ding, S. (2001, April). Profile analysis via multidimensional scaling (PAMS): Exploring the predominant profile patterns in data. Paper presented at the annual meeting of American Educational Research Association, Seattle, WA.

Ding, C. S. (2001). Profile analysis: Multidimensional scaling approach. Practical Assessment, Research, & Evaluation, 7(16), Retrieved May 10, 2019, from

OECD (The Organization for Economic Co-operation and Development). (2012). Connected minds: Technology and today’s learners, educational research and innovation. OECD Publishing. Retrieved from _9789264111011-en

Orhan, D., & Kurt, A. A. (2015, March). An Inventory for Determining 21st Century Learner Skills Usage: Validity and Reliability Study. In Society for Information Technology & Teacher Education International Conference (pp. 3522-3524). Association for the Advancement of Computing in Education (AACE).

Orhan Göksün, D. (2016). Öğretmen adaylarının 21. yy. öğrenen becerileri ve 21. yy. öğreten becerileri arasındaki ilişki. (Yayımlanmamış doktora tezi). Anadolu Üniversitesi, Eğitim Bilimleri Enstitüsü, Eskişehir, Türkiye.

R Core Team (2013). R: A language and environment for statistical computing [Computer software]. R foundation for statistical computing, Vienna, Austria.

Trilling, B. and Fadel, C. (2009). 21st century skills: Learning for life in our times: Learning for life in our times. John Wiley & Sons.

Wagner, T. (2008). The global achievement gap: Why even our best schools don't teach the new survival skills our children need-and what we can do about it. New York, NY: Basic Books.

Wrahatnolo, T. (2018, January). 21st centuries skill implication on educational system. In IOP Conference Series: Materials Science and Engineering (Vol. 296, No. 1, p. 012036). IOP Publishing.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

 ISSN: 1305-3515