Open Assessment Resources for Deeper Learning

Imagine a tutor or sessional instructor anywhere in the world who wishes to know something about what students know and can do. With knowledge about Open Assessment Resources (OAR), a repository is visited that is linked to many sites frequented by instructors and instructional designers. The website links existing OER activities with open assessment resource activity-prompts for online student responses. Within the assessment component of a selected OER, the instructor finds a searchable data bank of concepts linked to core content and activities related to what is being taught. The assessment activity-prompt packages can be made, modified or found an

Challenges for IT-Enabled Formative Assessment of Complex 21st Century Skills

In this article, we identify and examine opportunities for formative assessment provided by information technologies (IT) and the challenges which these opportunities present. We address some of these challenges by examining key aspects of assessment processes that can be facilitated by IT: datafication of learning; feedback and scaffolding; peer assessment and peer feedback. We then consider how these processes may be applied in relation to the assessment of horizontal, general complex 21st century skills (21st CS), which are still proving challenging to incorporate into curricula as well as to assess. 21st CS such as creativity, complex problem solving, communication, collaboration and self-regulated learning contain complex constructs incorporating motivational and affective components. Our analysis has enabled us to make recommendations for policy, practice and further research. While there is currently much interest in and some progress towards the development of learning/assessment analytics for assessing 21st CS, the complexity of assessing such skills, together with the need to include affective aspects means that using IT-enabled techniques will need to be combined with more traditional methods of teacher assessment as well as peer assessment for some time to come. Therefore learners, teachers and school leaders must learn how to manage the greater variety of sorts and sources of feedback including resolving tensions of inconsistent feedback from different sources

Thematic Working Group 5: Formative assessment supported by technology.

The future of assessment faces major challenges including the use of IT to facilitate formative assessment that is important for improving learners’ development, motivation and engagement in learning. In many countries, in recent years, a renewed focus on assessments to support learning has been pushing against the burgeoning of testing for accountability, which in some countries, renders effective formative assessment practices almost impossible. Moreover, a systematic review by Harlen and Deakin Crick (2002) revealed that a strong focus on summative assessment for accountability can reduce motivation and disengage many learners. At the same time use of IT‐enabled assessments has been increasing rapidly, as they offer promise of cheaper ways of delivering and marking assessments as well as access to vast amounts of assessment data from which a wide range of judgements might be made about students, teachers, schools and education systems (Gibson & Webb, 2015). These opportunities also extend to assessment of complex collaborative work (Webb & Gibson, 2015). Current opportunities for using IT, including for harnessing the data that is being collected automatically, for formative assessment are underexplored and less well understood than those for summative assessments. Opportunities for learning with IT and perhaps with less teacher input are increasing but this depends on students developing as autonomous or independent learners. Research in formative assessment including effective feedback has emphasised the value of peer assessment practices for developing self‐assessment capabilities and hence independent learners (Black, Harrison, Lee, Marshall, & William, 2003). At previous EDUsummITs the possibilities and challenges for IT‐enabled assessments to support simultaneously both formative and summative purposes were analysed (Webb, Gibson, & Forkosh‐Baruch, 2013). While these challenges remain, at EDUsummIT 2017 we focused on the opportunities and challenges of IT supporting formative assessment because effective formative assessment is known to be extremely important for learning.RETHINKING LEARNING IN A DIGITAL AGE, EDUsummIT 2017 Summary Reports 18-20 september, Bulgari

Measuring and understanding self-handicapping in education

Self-handicapping is intentionally fabricating obstacles to performance. It is very prevalent in education where it interferes with learning and lowers academic achievement. Few self-handicapping experiments have approximated authentic learning situations, elevating concerns about ecological validity and generalizability. This study addressed several methodological concerns by (a) posing a task common in education, and (b) offering participants multiple occasions to choose among several productive, neutral, or self-handicapping approaches to learning. Undergraduate learners were randomly assigned to receive contingent or non-contingent success feedback on three learning tasks. Each task offered multiple occasions to claim or practise self-handicapping by making selections within a component of the software. Those selections caused changes in the learning environment while participants worked on tasks and generated data about self-handicapping more realistically situated and in finer grain than data gathered in prior research. Results indicate this method for unobtrusively recording data about self-handicapping validly represented the construct. Learners’ choices reflected preferences for certain handicaps and described patterns of hidden versus blatant self-handicapping. Evidence for self-handicapping and self-regulated learning across tasks was found. Some learners repeatedly self-handicapped, Others self-regulated learning over time by demonstrating metacognitive awareness, monitoring, and control of learning activities regardless of feedback provided. Encouraging metacognition may aid self-handicappers to more productively self-regulate their learning over time

Una aproximación del efecto en el aprendizaje de una lengua extranjera debida a la obtención de datos a través de exámenes en línea de idiomas

Artificial intelligence oriented to education (AIEd) allows the adequacy and / or adaption to the user’s learning itineraries through inductive processes based on the extraction of data obtained from the formative evidences that it generates throughout its school life. Big data, or massive data, is the storage of large amounts of data that can be analyzed by various procedures and allows us to find repetitive patterns or predictive formulas that can generate learning about ourselves and especially the network. In the case of the massive data that are generated through the use of tests in the learning and certification of knowledge of languages as a foreign language at the national level, we find that it might be useful to apply Big Data's processing methodologies in order to know better if the information Generated through the tests can improve or create new learning strategies or establish formal criteria in the design of the tests, theories of second language acquisition, or even educational policies. The novelty of the article focuses on establishing viable guidelines to apply the more generic concepts of Big Data in the specific context of the tests of language evaluation as a second language and where there is a priori a large amount of information to be processed at the educational level. The article shows some guidelines that could be applied in the mechanisms used in the extraction of educational data from large-scale language learning in the specific environment of language assessment tests as a foreign language.La Inteligencia Artificial orientada a la educación (AIEd) permite adecuar y/o adaptar los itinerarios del aprendizaje de un usuario mediante procesos inductivos basados en la extracción de datos obtenidos de las evidencias formativas que genera a lo largo de su vida escolar. El Big data, o datos masivos es el almacenamiento de grandes cantidades de datos que pueden ser analizados por diversos procedimientos y que permite encontrar patrones repetitivos o formulas predictivas que pueden generar un aprendizaje sobre nosotros mismos y sobre todo en la red. En el caso de los datos masivos que se generan a través de los exámenes utilizados en el aprendizaje y certificación de conocimiento de idiomas como segunda lengua a nivel nacional encontramos que podría ser útil aplicar las metodologías de procesamiento del Big Data para conocer mejor si la información generada a través de los test pueden mejorar o crear nuevas estrategias de aprendizaje o establecer criterios formales en el diseño de las pruebas, teorías de adquisición de se segunda lengua o incluso políticas educativas. La novedad de artículo se centra en establecer directrices viables para aplicar los conceptos más genéricos del Big Data en el contexto específico de los test de evaluación de idiomas como segunda lengua y donde existe a priori una gran cantidad de información a procesar a nivel educativo. El artículo muestra algunas directrices que podrían aplicarse en los mecanismos aplicados en la extracción de datos educativos del aprendizaje de idiomas a gran escala en el entorno específico de los test de evaluación de idiomas como lengua extranjera

Putting learning back into learning analytics: actions for policy makers, researchers, and practitioners

This paper is based on (a) a literature review focussing on the impact of learning analytics on supporting learning and teaching, (b) a Delphi study involving international expert discussion on current opportunities and challenges of learning analytics as well as (c) outlining a research agenda for closing identified research gaps. Issues and challenges facing educators linked to learning analytics and current research gaps were organised into four themes, the further development of which by the expert panel, led to six strategy and action areas. The four themes are 1. development of data literacy in all stakeholders, 2. updating of guiding principles and policies of educational data, 3. standards needed for ethical practices with data quality assurance, and 4. flexible user-centred design for a variety of users of analytics, starting with learners and ensuring that learners and learning is not harmed. The strategies and actions are outcomes of the expert panel discussion and are offered as provocations to organise and focus the researcher, policymaker and practitioner dialogs needed to make progress in the field

Open Education

"This insightful collection of essays explores the ways in which open education can democratise access to education for all. It is a rich resource that offers both research and case studies to relate the application of open technologies and approaches in education settings around the world. Global in perspective, this book argues strongly for the value of open education in both the developed and developing worlds. Through a mixture of theoretical and practical approaches, it demonstrates that open education promotes ideals of inclusion, diversity, and social justice to achieve the vision of education as a fundamental human right. A must-read for practitioners, policy-makers, scholars and students in the field of education.

International Perspectives on School Settings, Education Policy and Digital Strategies. A Transatlantic Discourse in Education Research

Since 2015, the Office for International Cooperation in Education at DIPF | Leibniz Institute for Research and Information in Education has organized international sessions on education research at the Annual Meetings of the American Educational Research Association, thus providing a floor for transatlantic exchange on current research topics. The volume gives an overview of the transatlantic activities in education research with regard to these sessions. (DIPF/Orig.

International Perspectives on School Settings, Education Policy and Digital Strategies

An exchange on education ideas has shaped the transatlantic discourse in education for a long time. Over the past two decades education science has increasingly become networked internationally. Since 2015, the Office for International Cooperation in Education at DIPF | Leibniz Institute for Research and Information in Education has organized international sessions on education research at the Annual Meetings of the American Educational Research Association, thus providing a floor for transatlantic exchange on current research topics. The volume gives an overview of the transatlantic activities in education research with regard to these sessions representing a collection of topics ranging from school development over the use of large scale assessment and digital data in education to questions related to migration and public education or the economization of education. At the same time the volume offers a reflection on the assets and obstacles of international exchange

Digital agency to empower equity in education:Summary Report

In EDUsummIT 2017, Thematic Working Group (TWG) 4 researched digital agency empowering equity in education. In a world where digital engagement with learning is increasing, both onsite and online, it is important that concepts and concerns of digital agency are considered appropriately by policymakers and practitioners when they develop and implement provision for learners, locally, regionally, nationally and internationally