In all educational environment there are numerous forms of assessment. The two basics categories of assessment include formative assessment and summative assessment. The core purpose of formative assessment is to assist in the learning process of students while summative assessment is focused on determining what learning has taken place (Dolin et al, 2018). Irrespective of the type of assessment, both categories provide the teachers, but more importantly the students, with feedback. It is common knowledge that feedback is essential in all forms of education.

In the digital age of the 21st century, recursive feedback is being developed. It is a new concept relating to assessment in education that utilises “continuous machine-mediated human assessment” and “machine feedback” (Cope & Kalantzis, 2017). In the past the teacher provided one small piece of summative feedback, usually the grade (A-F), which evaluates the extent of learning achieved (Dolin et al, 2018). When using recursive feedback, there are numerous fragments of feedback obtained from the students’ peers, themselves and similarly the teacher. This provides a multitude of data that can be used to promote the learning process, before the final submission. Consequently, producing prospective and constructive feedback within a formative assessment paradigm (Cope & Kalantzis, 2017). It may also be possible to using computer programming to develop a set of responses based on the assessment input provided. This inevitably gives the feedback a formative perspective. Similarly, computer software is being developed that can understand and respond to text data (https://www.ibm.com). It should be obvious, that the recursive feedback methodologies will provide students with a multitude of feedback but the feedback would be provided within a relatively short timeframe.

In the near future, the development of recursive feedback with its integration of computer technology could lead to some dramatic changes of assessment in education. These include inserting the formative assessment into an e-learning lesson that will produce significant amounts of data based on students’ completion of their assignment. This immense amount of data may be used for immediate feedback and consequent improvements by students. Finally, it may lead to the replacement of standarised testing as we know it today (Cope & Kalantzis, 2017).

References:

Cope, B., & Kalantzis, M. (Eds.). (2017). E-learning ecologies: Principles for new learning and assessment. London, United Kingdom: Taylor & Francis.

Dolin, J., Black, P., Harlen, W., & Tiberghien, A. (2018). Exploring Relations Between Formative and Summative Assessment. In J. Dolin & R. Evans (Éd.), Transforming Assessment (Vol. 4, p. 53 80). Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-63248-3

Natural Language Processing (NLP). https://www.ibm.com/cloud/learn/natural-language-processing.