Assessing Student Learning with Technology: A Descriptive Study of Technology-Using Teacher Practice and Technological Pedagogical Content Knowledge (TPACK)

In 2013, a majority of states in the US had adopted Common Core State Standards under the Race to the Top initiative. With this adoption came the opportunity to utilize computer-delivered and computer-adaptive testing. Although the computer-based assessments were intended to assist teachers in designing classroom assessments and using student data to inform instructional practice, teacher-reported data indicated that the areas in which teachers are most unprepared, lack confidence, or are in need of development were assessment (DeLuca, 2012; Wayman et al., 2007) and technology (Brush & Saye, 2009; Kramarski & Michalsky, 2010). The Technology Assessment Practices Survey (TAPS) study was developed based on research in assessment literacy and in the technological pedagogical content knowledge framework. The purpose for developing this mixed-method study was the need to understand better how technology-using teachers assess student learning with technology. Two primary research questions facilitated a description of the assessment literacy and use of technology by 84 technology-using teachers. Participants in the study represented a diverse population of self-identified technology-using teachers. Quantitative and qualitative data were analyzed to provide insight into how technology-using teachers use technology to assess student learning. These data were analyzed for fitness with the TPACK theoretical model of teacher knowledge in order to fill an identified gap in the TPACK research (Cox & Graham, 2010). The TAPS study shows that technology-using teachers who belong to professional-education organizations have higher levels of confidence in both assessment and technology. Quantitative and qualitative data collected in the study also provides insight into the ways in which technology-using teachers think about, design, implement, and use the results of assessments in the classroom. Technology-using teachers exemplify TPACK, including attention to context at the macro, meso, and micro levels (Abbitt, 2011; Doering et al., 2009; Koehler & Mishra, 2009; Mishra & Koehler, 2005, 2006; Porras-Hernandez & Salinas-Amescua, 2013; Voogt et al., 2012). Future qualitative and quantitative research is needed into how preservice and inservice teachers use technology to assess student learning. Stakeholders in national, state, and local educational institutions need to consider how they are supporting the successful use of technology to assess student learning

Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments

Randomized experiments ensure robust causal inference that are critical to effective learning analytics research and practice. However, traditional randomized experiments, like A/B tests, are limiting in large scale digital learning environments. While traditional experiments can accurately compare two treatment options, they are less able to inform how to adapt interventions to continually meet learners' diverse needs. In this work, we introduce a trial design for developing adaptive interventions in scaled digital learning environments -- the sequential randomized trial (SRT). With the goal of improving learner experience and developing interventions that benefit all learners at all times, SRTs inform how to sequence, time, and personalize interventions. In this paper, we provide an overview of SRTs, and we illustrate the advantages they hold compared to traditional experiments. We describe a novel SRT run in a large scale data science MOOC. The trial results contextualize how learner engagement can be addressed through inclusive culturally targeted reminder emails. We also provide practical advice for researchers who aim to run their own SRTs to develop adaptive interventions in scaled digital learning environments

Reflective Journaling: A Theoretical Model and Digital Prototype for Developing Resilience and Creativity

Reflection is commonly discussed as a tool for personal and professional development that is becoming increasingly important in today’s global and digital world. In this paper, we propose a model that suggests ways in which reflection, in the form of Reflective Journaling, can support the development of creativity and resilience, which are needed to enable individuals to function effectively in a fast-changing environment. In addition, the model proposes ways in which external support and progress monitoring can be used in conjunction with skills in adaptive resilience and structured creativity, to support the maintenance of reflective journaling as a habit, in the longer term, thus creating virtuous cycles of skills and behaviours that can reinforce each other. Based on our model, and additional user research, we describe the design of a first digital prototype that aims to support the use of Reflective Journaling and to develop creativity and resilience through suggested mechanisms. Initial evaluations of our prototype are positive. It has been well-received by early test users, and has the potential to address all the connections defined. We therefore suggest that the theoretical model can be used to develop digital tools, such as the one included, to help those who wish to develop the habit of reflective journaling, and through that a range of other skills associated with resilience and creative thinking. We see this as a starting point for investigating this potential in more depth

Co-management: A Synthesis of the Lessons Learned from the DFID Fisheries Management Science Programme

For the last eleven years, the UK Department for International Development (DfID) have been funding research projects to support the sustainable management of fisheries resources (both inland and marine) in developing countries through the Fisheries Management Science Programme (FMSP). A number of these projects that have been commissioned in this time have examined fisheries co-management. While these projects have, for the most part, been implemented separately, the FMSP has provided an opportunity to synthesise and draw together some of the information generated by these projects. We feel that there is value in distilling some of the important lessons and describing some of the useful tools and examples and making these available through a single, accessible resource. The wealth of information generated means that it is impossible to cover everything in detail but it is hoped that this synthesis will at least provide an overview of the co-management process together with some useful information relating to implementing co-management in a developing country context and links to the more detailed re-sources available, in particular on information systems for co-managed fisheries, participatory fish stock assessment (ParFish) and adaptive learning that have, in particular, been drawn upon for this synthesis. This synthesis is aimed at anyone interested in fisheries management in a developing country context

Innovating Pedagogy 2015: Open University Innovation Report 4

This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This fourth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Center for Technology in Learning at SRI International. We proposed a long list of new educational terms, theories, and practices. We then pared these down to ten that have the potential to provoke major shifts in educational practice, particularly in post-school education. Lastly, we drew on published and unpublished writings to compile the ten sketches of new pedagogies that might transform education. These are summarised below in an approximate order of immediacy and timescale to widespread implementation

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Diagnosis and the management constituency of small-scale fisheries

Diagnosis and adaptive management can help improve the ability of small-scale fisheries (SSF) in the developing world to better cope with and adapt to both external drivers and internal sources of uncertainty. This paper presents a framework for diagnosis and adaptive management and discusses ways of implementing the first two phases of learning: diagnosis and mobilising an appropriate management constituency. The discussion addresses key issues and suggests suitable approaches and tools as well as numerous sources of further information. Diagnosis of a SSF defines the system to be managed, outlines the scope of the management problem in terms of threats and opportunities, and aims to construct realistic and desired future projections for the fishery. These steps can clarify objectives and lead to development of indicators necessary for adaptive management. Before management, however, it is important to mobilize a management constituency to enact change. Ways of identifying stakeholders and understanding both enabling and obstructive interactions and management structures are outlined. These preliminary learning phases for adaptive SSF management are expected to work best if legitimised by collaborative discussion among fishery stakeholders drawing on multiple knowledge systems and participatory approaches to assessment. (PDF contains 33 pages

Validation and Verification of Aircraft Control Software for Control Improvement

Validation and Verification are important processes used to ensure software safety and reliability. The Cooper-Harper Aircraft Handling Qualities Rating is one of the techniques developed and used by NASA researchers to verify and validate control systems for aircrafts. Using the Validation and Verification result of controller software to improve controller\u27s performance will be one of the main objectives of this process. Real user feedback will be used to tune PI controller in order for it to perform better. The Cooper-Harper Aircraft Handling Qualities Rating can be used to justify the performance of the improved system

Adaptive learning program for developing employability skills

The paper aims to demonstrate the benefits of adaptive learning technologies as a viable alternative to time consuming tutor led individual support. It proposes to reveal how adaptive learning interventions can be effective in enriching student learning while targeting precise areas of development. This review will compile evidence on the nature and extent of Adaptive Learning tools used to develop employability skills among Higher Education institutions. This will be specifically for students undergoing studies at the graduate level. Given the short time available, a scoping study framework will be used to examine the scope of carrying out a full systematic review or identifying gaps in existing literature (Arksey and O’Malley, 2005). This design follows the general principles of a systematic review by following pre‐specified methods to reduce the risk of bias by selecting favourable studies, and extracting and analysing data that backs a particular hypothesis. That is, the methods are determined a priori, and are transparent and replicable