Adaptive feedback in computer-based learning environments: a review

Abstract

Adaptive support within a learning environment is useful because most learners have different personal characteristics such as prior knowledge, learning progress, and learning preferences. This study reviews various implementation of adaptive feedback, based on the four adaptation characteristics: means, target, goal, and strategy. This review focuses on 20 different implementations of feedback in a computer-based learning environment, ranging from multimedia web-based intelligent tutoring systems, dialog-based intelligent tutoring systems, web-based intelligent e-learning systems, adaptive hypermedia systems, and adaptive learning environment. The main objective of the review is to compare computer-based learning environments according to their implementation of feedback and to identify open research questions in adaptive feedback implementations. The review resulted in categorizing these feedback implementations based on the students' information used for providing feedback, the aspect of the domain or pedagogical knowledge that is adapted to provide feedback based on the students' characteristics, the pedagogical reason for providing feedback, and the steps taken to provide feedback with or without students' participation. Other information such as the common adaptive feedback means, goals, and implementation techniques are identified. This review reveals a distinct relationship between the characteristics of feedback, features of adaptive feedback, and computer-based learning models. Other information such as the common adaptive feedback means, goals, implementation techniques, and open research questions are identified.

The Effectiveness of Blended Learning in Improving Students’ Workplace Communication Skills: A Case Study on Olive Website Test Result

“…They could identify what they still lack and look for strategies to improve it. Similar research also shows that providing feedback is useful because most learners have different characteristics, such as prior knowledge, learning pace, and learning preference (Bimba et al, 2017). By accessing the online-based listening materials, the students are given more chance to self-evaluate their communicative competence, improve their skills, and be responsible for learning.…”

Designing and Developing Videos for Online Learning: A Seven-Principle Model

“…Although this automated feedback works well with questions that have standardized answers, it still lacks the just-in-time feedback and guidance that instructors in the classroom can provide. Adaptive feedback could be a good solution for providing feedback in an asynchronous online learning environment, as it not only verifies the correctness of an answer but also provides different information for different answers (Bimba et al, 2017;Dempsey & Sales, 1993;Le, 2016).…”

Evaluation of Adaptive Feedback in a Smartphone-Based Game on Health Care Providers’ Learning Gain: Randomized Controlled Trial

“…This study has addressed some of the recommendations from a recent evidence review into gamified education in health, which proposed future studies to employ the use of a rigorous experimental design to evaluate learning interventions, and include more studies from low- and middle-income countries, two underrepresented aspects of the current evidence base [ 15 ]. Even when considering interventions looking into adaptive feedback in digital education, none that we know of are in the health domain [ 71 ], making this study unique. Given that the implementation of the learning intervention was available to all clinical cadres involved with bedside care provision, who had varying levels of experience (from students to consultants), from multiple low-income countries, representing a varied mix of geographical and resource settings, the diverse population of the clinical taskforce in this experiment ensures that those who would most benefit from using the presented learning tool for training in emergency care delivery are well represented.…”