Adapting the automatic assessment of free-text answers to the students

In this paper, we present the first approach in the field of Computer Assisted Assessment (CAA) of students' free-text answers to model the student profiles. This approach has been implemented in a new version of Atenea, a system able to automatically assess students' short answers. The system has been improved so that it is now able to take into account the students' preferences and personal features to adapt not only the assessment process but also to personalize the appearance of the interface. In particular, it is now able to accept students’ answers written in Spanish or in English indistinctly, by means of Machine Translation. Moreover, we have observed that Atenea’s performance does not decrease drastically when combined with automatic translation, provided that the translation does not reduce greatly the variability in the vocabulary

Learning through assessment

This book aims to contribute to the discourse of learning through assessment within a self-directed learning environment. It adds to the scholarship of assessment and self-directed learning within a face-to-face and online learning environment. As part of the NWU Self-Directed Learning Book Series, this book is devoted to scholarship in the field of self-directed learning, focusing on ongoing and envisaged assessment practices for self-directed learning through which learning within the 21st century can take place. This book acknowledges and emphasises the role of assessment as a pedagogical tool to foster self-directed learning during face-to-face and online learning situations. The way in which higher education conceptualises teaching, learning and assessment has been inevitably changed due to the COVID- 19 pandemic, and now more than ever we need learners to be self-directed in their learning. Assessment plays a key role in learning and, therefore, we have to identify innovative ways in which learning can be assessed, and which are likely to become the new norm even after the pandemic has been brought under control. The goal of this book, consisting of original research, is to assist with the paradigm shift regarding the purpose of assessment, as well as providing new ideas on assessment strategies, methods and tools appropriate to foster self-directed learning in all modes of delivery

Learning through assessment

This book aims to contribute to the discourse of learning through assessment within a self-directed learning environment. It adds to the scholarship of assessment and self-directed learning within a face-to-face and online learning environment. As part of the NWU Self-Directed Learning Book Series, this book is devoted to scholarship in the field of self-directed learning, focusing on ongoing and envisaged assessment practices for self-directed learning through which learning within the 21st century can take place. This book acknowledges and emphasises the role of assessment as a pedagogical tool to foster self-directed learning during face-to-face and online learning situations. The way in which higher education conceptualises teaching, learning and assessment has been inevitably changed due to the COVID- 19 pandemic, and now more than ever we need learners to be self-directed in their learning. Assessment plays a key role in learning and, therefore, we have to identify innovative ways in which learning can be assessed, and which are likely to become the new norm even after the pandemic has been brought under control. The goal of this book, consisting of original research, is to assist with the paradigm shift regarding the purpose of assessment, as well as providing new ideas on assessment strategies, methods and tools appropriate to foster self-directed learning in all modes of delivery

Distributed adaptive e-assessment in a higher education environment

The rapid growth of Information Communication Technology (ICT) has promoted the development of paperless assessment. Most of the e-Assessment systems available nowadays, whether as an independent system or as a built-in module of a Virtual Learning Environment (VLE), are fixed-form e-Assessment systems based on the Classical Test Theory (CTT). In the meantime, the development of psychometrics has also proven the potential for e-Assessment systems to benefit from adaptive assessment theories. This research focuses on the applicability of adaptive e-Assessment in daily teaching and attempts to create an extensible web-based framework to accommodate different adaptive assessment strategies for future research. Real-data simulation and Monte Carlo simulation were adopted in the study to examine the performance of adaptive e-Assessment in a real environment and an ideal environment respectively. The proposed framework employs a management service as the core module which manages the connection from distributed test services to coordinate the assessment. The results of this study indicate that adaptive e-Assessment can reduce test length compared to fixed-form e-Assessment, while maintaining the consistency of the psychometric properties of the test. However, for a precise ability measurement, even a simple adaptive assessment model would demand a sizable question bank with ideally over 200 questions on a single latent trait. The requirements of the two categories of stakeholders (pedagogical researchers and educational application developers), as well as the variety and complexity of adaptive models, call for a framework with good accessibility for users, considerable extensibility and flexibility for implementing different assessment models, and the ability to deliver excessive computational power in extreme cases. The designed framework employs a distributed architecture with cross-language support based on the Apache Thrift framework to allow flexible collaboration of users with different programming language skills. The framework also allows different functional components to be deployed distributedly and to collaborate over a networ

Adaptive computer assisted assessment of free-text students' answers: an approach to automatically generate students' conceptual models

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, mayo de 200

Problem solving with Adaptive Feedback

Abstract. The virtual laboratory (VILAB) supports interactive problem solving in computer science with access to complex software-tools. During the problem solving processes the learners get fast feedback by a tutoring component. This feedback based in the first version of VI-LAB only on intelligent error analyses of learners ’ solutions. Animated by the very positive results of the evaluation of this tutoring component we additionally implemented an user model. Thereby the feedback for a learner consists not only of adaptive information about his errors and performance, but also of adaptive hints for the improvement of his solution. Furthermore, the tutoring component can individually motivate the learners.