Characteristics of Feedback that Influence Student Confidence and Performance during Mathematical Modeling

This study focuses on characteristics of written feedback that influence students’ performance and confidence in addressing the mathematical complexity embedded in a Model-Eliciting Activity (MEA). MEAs are authentic mathematical modeling problems that facilitate students’ iterative development of solutions in a realistic context. We analyzed 132 first-year engineering students’ confidence levels and mathematical model scores on aMEA(pre and post feedback), along with teaching assistant feedback given to the students. The findings show several examples of affective and cognitive feedback that students reported that they used to revise their models. Students’ performance and confidence in developing mathematical models can be increased when they are in an environment where they iteratively develop models based on effective feedback

Failure is an option:an innovative engineering curriculum

PurposeAdvancements and innovation in engineering design are based on learning from previous failures but students are encouraged to ‘succeed’ first time and hence can avoid learning from failure in practice. The purpose of the study was to design and evaluate a curriculum to help engineering design students to learn from failure.Design/Methodology/ApproachA new curriculum design provided a case study for evaluating the effects of incorporating learning from failure within a civil engineering course. An analysis of the changes in course output was undertaken in relation to graduate destination data covering 2006 to 2016 and student satisfaction from 2012 to 2017 and a number of challenges and solutions for curriculum designers were identified.FindingsThe design and delivery of an innovative curriculum, within typical constraints, can provide opportunities for students to develop resilience to failure as an integral part of their learning in order to think creatively and develop novel engineering solutions. The key issues identified were: the selection of appropriate teaching methods, creating an environment for exploratory learning, group and team assessments with competitive elements where practicable, and providing students with many different pedagogical approaches to produce a quality learning experience.OriginalityThis case study demonstrates how to design and implement an innovative curriculum that can produce positive benefits of learning from failure. This model can be applied to other disciplines such as building surveying and construction management. This approach underpins the development of skills necessary in the educational experience to develop as a professional building pathologist

Course developers as students: a designer perspective of the experience of learning online

Academic developers of online courses may not have experienced this mode of learning and teaching from the learner perspective. This article makes a comparison between suggestions for online course design from research literature and user perspectives from a focus group, responses to questions on the most and least effective aspects of online study and lasting impressions, and from reflective diaries kept by two of the authors while they were engaged in study from online courses. This direct evidence is used to highlight key issues in the literature from the viewpoint of the learner

Artificial Intelligence And Big Data Technologies To Close The Achievement Gap.

We observe achievement gaps even in rich western countries, such as the UK, which in principle have the resources as well as the social and technical infrastructure to provide a better deal for all learners. The reasons for such gaps are complex and include the social and material poverty of some learners with their resulting other deficits, as well as failure by government to allocate sufficient resources to remedy the situation. On the supply side of the equation, a single teacher or university lecturer, even helped by a classroom assistant or tutorial assistant, cannot give each learner the kind of one-to-one attention that would really help to boost both their motivation and their attainment in ways that might mitigate the achievement gap. In this chapter Benedict du Boulay, Alexandra Poulovassilis, Wayne Holmes, and Manolis Mavrikis argue that we now have the technologies to assist both educators and learners, most commonly in science, technology, engineering and mathematics subjects (STEM), at least some of the time. We present case studies from the fields of Artificial Intelligence in Education (AIED) and Big Data. We look at how they can be used to provide personalised support for students and demonstrate that they are not designed to replace the teacher. In addition, we also describe tools for teachers to increase their awareness and, ultimately, free up time for them to provide nuanced, individualised support even in large cohorts

A hybrid method for the analysis of learner behaviour in active learning environments

Software-mediated learning requires adjustments in the teaching and learning process. In particular active learning facilitated through interactive learning software differs from traditional instructor-oriented, classroom-based teaching. We present behaviour analysis techniques for Web-mediated learning. Motivation, acceptance of the learning approach and technology, learning organisation and actual tool usage are aspects of behaviour that require different analysis techniques to be used. A hybrid method based on a combination of survey methods and Web usage mining techniques can provide accurate and comprehensive analysis results. These techniques allow us to evaluate active learning approaches implemented in form of Web tutorials

Contemporary developments in teaching and learning introductory programming: Towards a research proposal

The teaching and learning of introductory programming in tertiary institutions is problematic. Failure rates are high and the inability of students to complete small programming tasks at the completion of introductory units is not unusual. The literature on teaching programming contains many examples of changes in teaching strategies and curricula that have been implemented in an effort to reduce failure rates. This paper analyses contemporary research into the area, and summarises developments in the teaching of introductory programming. It also focuses on areas for future research which will potentially lead to improvements in both the teaching and learning of introductory programming. A graphical representation of the issues from the literature that are covered in the document is provided in the introduction

Towards better integration of environmental science in society: lessons from BONUS, the joint Baltic Sea environmental research and development programme

Integration of environmental science in society is impeded by the large gap between science and policy that is characterised by weaknesses in societal relevance and dissemination of science and its practical implementation in policy. We analyse experiences from BONUS, the policy-driven joint Baltic Sea research and development programme (2007–2020), which is part of the European Research Area (ERA) and involves combined research funding by eight EU member states. The ERA process decreased fragmentation of Baltic Sea science and BONUS funding increased the scientific quality and societal relevance of Baltic Sea science and strengthened the science-policy interface. Acknowledging the different drivers for science producers (academic career, need for funding, peer review) and science users (fast results fitting policy windows), and realising that most scientists aim at building conceptual understanding rather than instrumental use, bridges can be built through strategic planning, coordination and integration. This requires strong programme governance stretching far beyond selecting projects for funding, such as coaching, facilitating the sharing of infrastructure and data and iterative networking within and between science producer and user groups in all programme phases. Instruments of critical importance for successful science-society integration were identified as: (1) coordinating a strategic research agenda with strong inputs from science, policy and management, (2) providing platforms where science and policy can meet, (3) requiring cooperation between scientists to decrease fragmentation, increase quality, clarify uncertainties and increase consensus about environmental problems, (4) encouraging and supporting scientists in disseminating their results through audience-tailored channels, and (5) funding not only primary research but also synthesis projects that evaluate the scientific findings and their practical use in society – in close cooperation with science users − to enhance relevance, credibility and legitimacy of environmental science and expand its practical implementation