What is the innovation beyond the 'state of the art' in e-learning?

Original article can be found at: www.herts.ac.uk/blip Copyright University of HertfordshireThe motivation for this discussion paper comes from the recent FP7 framework ICT call for technology-enhanced learning applications for the 21st century that go beyond the current “state of the art” in e-learning. In this paper the question of the innovation be-yond the “state of the art” in e-learning is considered along with identification and dis-cussion of some of its defining characteristics in the context of higher education. A re-view and analysis of innovative learning applications and models is presented, with a specific focus on learning environments, and learning interactions. The University of Hertfordshire is used to provide an example of a “state of the art” University regarding the adoption of e-learning applications and methods in day-to-day learning and teaching practice. It is suggested that innovative and “beyond the state of art” e-learning models, tools and applications will be required to support high degrees of personalization and collaboration.Peer reviewe

Design and evaluation of an ontology-based tool for generating multiple-choice questions

© 2020 Emerald Publishing Limited. This accepted manuscript is deposited under the Creative Commons Attribution Non-commercial International Licence 4.0 (CC BY-NC 4.0). Any reuse is allowed in accordance with the terms outlined by the licence, here: https://creativecommons.org/licenses/by-nc/4.0/. To reuse the AAM for commercial purposes, permission should be sought by contacting [email protected]: The recent rise in online knowledge repositories and use of formalism for structuring knowledge, such as ontologies, has provided necessary conditions for the emergence of tools for generating knowledge assessment. These tools can be used in a context of interactive computer-assisted assessment (CAA) to provide a cost-effective solution for prompt feedback and increased learner’s engagement. The purpose of this paper is to describe and evaluate a tool developed by the authors, which generates test questions from an arbitrary domain ontology, based on sound pedagogical principles encapsulated in Bloom’s taxonomy. Design/methodology/approach: This paper uses design science as a framework for presenting the research. A total of 5,230 questions were generated from 90 different ontologies and 81 randomly selected questions were evaluated by 8 CAA experts. Data were analysed using descriptive statistics and Kruskal–Wallis test for non-parametric analysis of variance.FindingsIn total, 69 per cent of generated questions were found to be useable for tests and 33 per cent to be of medium to high difficulty. Significant differences in quality of generated questions were found across different ontologies, strategies for generating distractors and Bloom’s question levels: the questions testing application of knowledge and the questions using semantic strategies were perceived to be of the highest quality. Originality/value: The paper extends the current work in the area of automated test generation in three important directions: it introduces an open-source, web-based tool available to other researchers for experimentation purposes; it recommends practical guidelines for development of similar tools; and it proposes a set of criteria and standard format for future evaluation of similar systems.Peer reviewedFinal Accepted Versio

Ancient and historical DNA in conservation policy

Although genetic diversity has been recognized as a key component of biodiversity since the first Convention on Biological Diversity (CBD) in 1993, it has rarely been included in conservation policies and regulations. Even less appreciated is the role that ancient and historical DNA (aDNA and hDNA, respectively) could play in unlocking the temporal dimension of genetic diversity, allowing key conservation issues to be resolved, including setting baselines for intraspecies genetic diversity, estimating changes in effective population size (N-e), and identifying the genealogical continuity of populations. Here, we discuss how genetic information from ancient and historical specimens can play a central role in preserving biodiversity and highlight specific conservation policies that could incorporate such data to help countries meet their CBD obligations.Peer reviewe

On the Use of Semantic-Based AIG to Automatically Generate Programming Exercises

In introductory programming courses, proficiency is typically achieved through substantial practice in the form of relatively small assignments and quizzes. Unfortunately, creating programming assignments and quizzes is both, time-consuming and error-prone. We use Automatic Item Generation (AIG) in order to address the problem of creating numerous programming exercises that can be used for assignments or quizzes in introductory programming courses. AIG is based on the use of test-item templates with embedded variables and formulas which are resolved by a computer program with actual values to generate test-items. Thus, hundreds or even thousands of test-items can be generated with a single test-item template. We present a semantic-based AIG that uses linked open data (LOD) and automatically generates contextual programming exercises. The approach was incorporated into an existing self-assessment and practice tool for students learning computer programming. The tool has been used in different introductory programming courses to generate a set of practice exercises different for each student, but with the same difficulty and quality

Monitoring of species' genetic diversity in Europe varies greatly and overlooks potential climate change impacts.

Genetic monitoring of populations currently attracts interest in the context of the Convention on Biological Diversity but needs long-term planning and investments. However, genetic diversity has been largely neglected in biodiversity monitoring, and when addressed, it is treated separately, detached from other conservation issues, such as habitat alteration due to climate change. We report an accounting of efforts to monitor population genetic diversity in Europe (genetic monitoring effort, GME), the evaluation of which can help guide future capacity building and collaboration towards areas most in need of expanded monitoring. Overlaying GME with areas where the ranges of selected species of conservation interest approach current and future climate niche limits helps identify whether GME coincides with anticipated climate change effects on biodiversity. Our analysis suggests that country area, financial resources and conservation policy influence GME, high values of which only partially match species' joint patterns of limits to suitable climatic conditions. Populations at trailing climatic niche margins probably hold genetic diversity that is important for adaptation to changing climate. Our results illuminate the need in Europe for expanded investment in genetic monitoring across climate gradients occupied by focal species, a need arguably greatest in southeastern European countries. This need could be met in part by expanding the European Union's Birds and Habitats Directives to fully address the conservation and monitoring of genetic diversity

Monitoring of species’ genetic diversity in Europe varies greatly and overlooks potential climate change impacts

Genetic monitoring of populations currently attracts interest in the context of the Convention on Biological Diversity but needs long-term planning and investments. However, genetic diversity has been largely neglected in biodiversity monitoring, and when addressed, it is treated separately, detached from other conservation issues, such as habitat alteration due to climate change. We report an accounting of efforts to monitor population genetic diversity in Europe (genetic monitoring effort, GME), the evaluation of which can help guide future capacity building and collaboration towards areas most in need of expanded monitoring. Overlaying GME with areas where the ranges of selected species of conservation interest approach current and future climate niche limits helps identify whether GME coincides with anticipated climate change effects on biodiversity. Our analysis suggests that country area, financial resources and conservation policy influence GME, high values of which only partially match species’ joint patterns of limits to suitable climatic conditions. Populations at trailing climatic niche margins probably hold genetic diversity that is important for adaptation to changing climate. Our results illuminate the need in Europe for expanded investment in genetic monitoring across climate gradients occupied by focal species, a need arguably greatest in southeastern European countries. This need could be met in part by expanding the European Union’s Birds and Habitats Directives to fully address the conservation and monitoring of genetic diversity

SeMCQ – Protégé Plugin for Automatic Ontology-Driven Multiple Choice Question Tests Generation

Paper can be found at: http://protege.stanford.edu/conference/2009/poster-session.html Copyright © 2010 Stanford Center for Biomedical Informatics ResearchCreating fair and meaningful assessment strategy is one the most difficult areas for every educator. Objective (MCQ) testing has been extensively studied and evaluated as a method for formative and, to a lesser extent, summative assessment. While the objective tests need to be complemented by other assessment strategies in order to assess higher cognitive domains, they nonetheless provide important benefits that are directly addressing the student needs such as, providing prompt and frequent feedback (2008 UK National Students Survey [8]). Moreover, in its more advanced forms, such as Computer-Adaptive Testing, objective tests can “get closer to measuring skills and intelligence” [3]. However, creating a useful objective test is not only difficult but also very time-consuming, which prevents its more wide-spread adoption and use [1]. In this paper we are trying to address this problem, by providing a framework and a prototype of a Semantic Multiple Choice Questions (SeMCQ) generator for an arbitrary knowledge domain. The prototype is implemented as a Protégé plugin. In the following sections we describe the implementation details of the prototype as well as some areas of future work.Final Accepted Versio