Abstract:

Assessment practice is formative to the extent that evidence about student achievement is elicited, interpreted, and used by teachers, learners, or their peers, to make decisions about the next steps in instruction. The key element for this purpose to be achieved is feedback.

Overcoming the traditional conception of feedback as unidirectional and finalist information, currently feedback is understood as the process by which learners make sense of the information they receive from different sources and use it to improve their work and/or learning strategies. That’s the reason why information and comments could be provided by teacher, peers, self, learning analytics dashboards, chatbots, etc. and the educational design should be focused on the actions that students will take with that information.

There is a new paradigm in progress where internal feedback seems to be a cornerstone. Internal feedback, external feedback, evaluative judgement, feedback as uptake, self-regulated learning, metacognition, feedback literacy are some key constructs of this paradigm. Most of them has bidirectional relationships but some clarification about how these concepts are connected is necessary in order a founded theory could be built.

The research on internal feedback in the educational context is at a crucial stage of development, where the construction of a solid theoretical framework is essential for a proper understanding of this construct. Through an integrative approach to key concepts such as internal feedback, external feedback, evaluative judgment, feedback uptake, self-regulated learning, metacognition, and feedback literacy, this work suggest that a coherent theoretical foundation can be established to advance towards a deeper understanding of feedback in the educational process. Specifically, it is proposed that the application of artificial intelligence tools, such as Algor 8, can significantly facilitate the systematization and analysis of data in educational research, providing a promising example of technology integration to enhance research processes in this field.

This paper shows a review of 8 papers from Web of Science chosen for having “internal feedback” in the title, being published in the last 5 years and belonging to educational research area. From the theoretical framework of each paper, where the main concepts and relationship among these concepts is stated, a fragment no longer than 15000 characters was selected. It was uploaded to free version of Algor 8 with different email accounts and 8 mind maps were created. These maps were compared by two independent researchers in a work session and integrated into final version of map.

The paper achieves two main contributions: the final proposal of mapping internal feedback, offering a theoretical framework for this construct to be understood but, at the same time, it offers an example of how AI could be used as an assistant in research processes.

Keywords:

Feedback, higher education, self-regulated learning.