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1.
Most distance learning institutions collect vast amounts of learning data. Making sense of this ‘Big Data’ can be a challenge, in particular when data are stored at different data warehouses and require advanced statistical skills to interpret complex patterns of data. As a leading institute on learning analytics, the Open University UK instigated in 2012 a Data Wrangling initiative. This provided every Faculty with a dedicated academic with expertise data analysis and whose task is to provide strategic, pedagogical and sense-making advice to staff and senior management. Given substantial changes within the OU (e.g. new Faculty structure, real-time dashboards, two large-scale adoptions of predictive analytics approaches, increased reliance on analytics), this embedded case study provides an in-depth review of lessons learned of five years of data wrangling. We will elaborate on the design of the new structure, its strengths and potential weaknesses, and affordances to be adopted by other institutions.  相似文献   

2.
ABSTRACT

Understanding and working with ethical issues when including young children in educational research is critical to ensuring their involvement is meaningful. Increasingly, different methodological approaches have been used to address some of these issues, and the use of visual methods is showing particular potential for its age appropriateness. This paper will specifically focus on three examples of drawing based visual method used with samples of children across compulsory school age from the Learning to Learn in Schools project: Pupil View Templates (n?=?263, age range 4–12 years), cartoon storyboards (n?=?210, age range 4–16 years) and fortune lines (n?=?69, 4–14 years). The discussion of each method will be framed from a pragmatic perspective and will particularly focus on the ethics of process and output, how the method was used and the data that were analysed. Questions will be asked about the considerations that need to be made when including young children in data sets with other older school-aged children and dilemmas identified: the affordances and constraints of visual approaches for all participants, the role of the visual as mediator, the role and positioning of the adult support and the impact this has on the nature of the data elicited.  相似文献   

3.
This paper addresses an issue of increasing significance in the context of taught educational doctorates and argues that this may have wider applicability for doctoral students across a range of social science disciplines. It identifies the need to engage with policy analysis as a key element of such programmes and attempts to address students' concerns over a lack of practical approaches to do so by offering an analytical framework drawing on critical discourse analysis. This paper highlights the affordances of a taught doctorate context to consider the potential for more collaborative community approaches to doctoral pedagogies through reflecting upon the way the frame was introduced and used by one group of EdD students. In doing so, this paper offers both a practical analytical tool for doctoral students but also a pedagogical approach grounded in an invitation to dialogue and induction into the academic discourse community, through a notion of critical inclusion.  相似文献   

4.
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5.
This case study is based on a research through design project (RTD) that focuses on a technical communication video of the live-action format. It investigates the usability and design-implications of a live-action how-to video, by means of analyzing user-centered data such as YouTube analytics data, usability, and comprehension assessments. In the study, four key live-action video affordances are identified: verifiability, comparability, recordability, and visibility. The identification of these affordances when related to the users’ assessments resulted in several design implementations that would warrant sought-for communication efficacies. Findings show that some assumed efficacies appear to be mitigated by the complexity and the density of the video information. One implication of this is that the implementation of conventional video editing techniques and the addition of on-screen text that serve to make content briefer and more concise into instructional live-action videos requires the technical communicator’s careful consideration.  相似文献   

6.
This study proposes a new methodological approach to evaluate students’ knowledge-building discourse. First, we discuss the knowledge–creation metaphor of learning. In the metaphor, theories mention that learners should consider their collective knowledge objects or artifacts that materialize as a result of their collaborative discourse. Second, we argue the necessity of developing new analytics to evaluate student learning. We describe how students’ ideas and their conceptual artifacts can be examined in discourse analysis. Third, we demonstrate the application of our analytics to real discourse data. We conducted a new type of social network analysis of discourse to examine how students continuously improve their ideas. Further, we conducted another network analysis of discourse, called the Epistemic Network Analysis, by coding students’ epistemic actions as conceptual artifacts to create and examine their ideas.  相似文献   

7.
Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes. The recent development of trace-based assessment has enabled innovative opportunities to overcome the problem. Despite the potential of a trace-based approach to study SSRL, there remains a paucity of evidence on how trace-based evidence could be captured and utilised to assess and promote SSRL. This study aims to investigate the assessment of electrodermal activities (EDA) data to understand and support SSRL in collaborative learning, hence enhancing learning outcomes. The data collection involves secondary school students (N = 94) working collaboratively in groups through five science lessons. A multimodal data set of EDA and video data were examined to assess the relationship among shared arousals and interactions for SSRL. The results of this study inform the patterns among students' physiological activities and their SSRL interactions to provide trace-based evidence for an adaptive and maladaptive pattern of collaborative learning. Furthermore, our findings provide evidence about how trace-based data could be utilised to predict learning outcomes in collaborative learning.

Practitioner notes

What is already known about this topic
  • Socially shared regulation has been recognised as an essential aspect of collaborative learning success.
  • It is challenging to make the processes of learning regulation ‘visible’ to better understand and support student learning, especially in dynamic collaborative settings.
  • Multimodal learning analytics are showing promise for being a powerful tool to reveal new insights into the temporal and sequential aspects of regulation in collaborative learning.
What this paper adds
  • Utilising multimodal big data analytics to reveal the regulatory patterns of shared physiological arousal events (SPAEs) and regulatory activities in collaborative learning.
  • Providing evidence of using multimodal data including physiological signals to indicate trigger events in socially shared regulation.
  • Examining the differences of regulatory patterns between successful and less successful collaborative learning sessions.
  • Demonstrating the potential use of artificial intelligence (AI) techniques to predict collaborative learning success by examining regulatory patterns.
Implications for practice and/or policy
  • Our findings offer insights into how students regulate their learning during collaborative learning, which can be used to design adaptive supports that can foster students' learning regulation.
  • This study could encourage researchers and practitioners to consider the methodological development incorporating advanced techniques such as AI machine learning for capturing, processing and analysing multimodal data to examine and support learning regulation.
  相似文献   

8.
ABSTRACT

In this article, I highlight findings from a nine-day unit embedded within a larger, four-month long qualitative action research study set in a public middle school. My goal in conducting this research was examination of relationships between visual culture and art integration as a method of fostering students to find voice while taking risks. A collaborative process was central to the unit in which the non-art educator and I developed and taught persuasion using art and art history. Students engaged in creating collaborative ecological installations, the integration of visual culture bridged art and other curricular areas while creating spaces for authentic learning. Through making art, students built shared knowledge, engaged in safe discourse, and expressed empathy.  相似文献   

9.
This article reports on a trace-based assessment of approaches to learning used by middle school aged children who interacted with NASA Mars Mission science, technology, engineering and mathematics (STEM) games in Whyville, an online game environment with 8 million registered young learners. The learning objectives of two games included awareness and knowledge of NASA missions, developing knowledge and skills of measurement and scaling, applying measurement for planetary comparisons in the solar system. Trace data from 1361 interactions were analysed with nonparametric multidimensional scaling methods, which permitted visual examination and statistical validation, and provided an example and proof of concept for the multidimensional scaling approach to analysis of time-based behavioural data from a game or simulation. Differences in approach to learning were found illustrating the potential value of the methodology to curriculum and game-based learning designers as well as other creators of online STEM content for pre-college youth. The theoretical framework of the method and analysis makes use of the Epistemic Network Analysis toolkit as a post hoc data exploration platform, and the discussion centres on issues of semantic interpretation of interaction end-states and the application of evidence centred design in post hoc analysis.

Practitioner notes

What is already known about this topic
  • Educational game play has been demonstrated to positively affect learning performance and learning persistence.
  • Trace-based assessment from digital learning environments can focus on learning outcomes and processes drawn from user behaviour and contextual data.
  • Existing approaches used in learning analytics do not (fully) meet criteria commonly used in psychometrics or for different forms of validity in assessment, even though some consider learning analytics a form of assessment in the broadest sense.
  • Frameworks of knowledge representation in trace-based research often include concepts from cognitive psychology, education and cognitive science.
What this paper adds
  • To assess skills-in-action, stronger connections of learning analytics with educational measurement can include parametric and nonparametric statistics integrated with theory-driven modelling and semantic network analysis approaches widening the basis for inferences, validity, meaning and understanding from digital traces.
  • An expanded methodological foundation is offered for analysis in which nonparametric multidimensional scaling, multimodal analysis, epistemic network analysis and evidence-centred design are combined.
Implications for practice and policy
  • The new foundations are suggested as a principled, theory-driven, embedded data collection and analysis framework that provides structure for reverse engineering of semantics as well as pre-planning frameworks that support creative freedom in the processes of creation of digital learning environments.
  相似文献   

10.
The field of learning analytics has advanced from infancy stages into a more practical domain, where tangible solutions are being implemented. Nevertheless, the field has encountered numerous privacy and data protection issues that have garnered significant and growing attention. In this systematic review, four databases were searched concerning privacy and data protection issues of learning analytics. A final corpus of 47 papers published in top educational technology journals was selected after running an eligibility check. An analysis of the final corpus was carried out to answer the following three research questions: (1) What are the privacy and data protection issues in learning analytics? (2) What are the similarities and differences between the views of stakeholders from different backgrounds on privacy and data protection issues in learning analytics? (3) How have previous approaches attempted to address privacy and data protection issues? The results of the systematic review show that there are eight distinct, intertwined privacy and data protection issues that cut across the learning analytics cycle. There are both cross-regional similarities and three sets of differences in stakeholder perceptions towards privacy and data protection in learning analytics. With regard to previous attempts to approach privacy and data protection issues in learning analytics, there is a notable dearth of applied evidence, which impedes the assessment of their effectiveness. The findings of our paper suggest that privacy and data protection issues should not be relaxed at any point in the implementation of learning analytics, as these issues persist throughout the learning analytics development cycle. One key implication of this review suggests that solutions to privacy and data protection issues in learning analytics should be more evidence-based, thereby increasing the trustworthiness of learning analytics and its usefulness.

Practitioner notes

What is already known about this topic
  • Research on privacy and data protection in learning analytics has become a recognised challenge that hinders the further expansion of learning analytics.
  • Proposals to counter the privacy and data protection issues in learning analytics are blurry; there is a lack of a summary of previously proposed solutions.
What this study contributes
  • Establishment of what privacy and data protection issues exist at different phases of the learning analytics cycle.
  • Identification of how different stakeholders view privacy, similarities and differences, and what factors influence their views.
  • Evaluation and comparison of previously proposed solutions that attempt to address privacy and data protection in learning analytics.
Implications for practice and/or policy
  • Privacy and data protection issues need to be viewed in the context of the entire cycle of learning analytics.
  • Stakeholder views on privacy and data protection in learning analytics have commonalities across contexts and differences that can arise within the same context. Before implementing learning analytics, targeted research should be conducted with stakeholders.
  • Solutions that attempt to address privacy and data protection issues in learning analytics should be put into practice as far as possible to better test their usefulness.
  相似文献   

11.
Background Psychology and educational theory has a long tradition of research into learning styles. However, the current educational policy and practice interest in learning styles in the UK has resulted in concepts and practices being adopted with little rigorous empirical evaluation.

Purpose This small-scale, experimental study aimed to test the reliability and validity of an available inventory designed to identify learning styles (visual, auditory and kinaesthetic).

Sample, design and methods Nineteen children, aged 7–10 years, with different styles as identified by the inventory, participated in a class experimental evaluation of their differential response to the teaching of word spelling using different teaching methods.

Results The study found that the visual and auditory scales, but not the kinaesthetic scale, were reliable (internally and re-test). The three groups of pupils with different learning styles—visual only, auditory only and mixed visual and auditory—showed different gains to teaching that matched these styles (visual and auditory teaching approaches). Retention of word spelling was higher one week after the teaching when the teaching matched the learning style.

Conclusions The findings in this exploratory study suggest the significance of learning style for classroom-based teaching.  相似文献   

12.
The field of learning design studies how to support teachers in devising suitable activities for their students to learn. The field of learning analytics explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and fragmented work exploring the active role that data analytics can play in supporting design for learning. This paper builds on previous research to propose a framework (analytics layers for learning design) that articulates three layers of data analytics—learning analytics, design analytics and community analytics—to support informed decision-making in learning design. Additionally, a set of tools and experiences are described to illustrate how the different data analytics perspectives proposed by the framework can support learning design processes.  相似文献   

13.
With digitisation and the rise of e‐learning have come a range of computational tools and approaches that have allowed educators to better support the learners' experience in schools, colleges and universities. The move away from traditional paper‐based course materials, registration, admissions and support services to the mobile, always‐on and always accessible data has driven demand for information and generated new forms of data observable through consumption behaviours. These changes have led to a plethora of data sets that store learning content and track user behaviours. Most recently, new data analytics approaches are creating new ways of understanding trends and behaviours in students that can be used to improve learning design, strengthen student retention, provide early warning signals concerning individual students and help to personalise the learner's experience. This paper proposes a foundational learning analytics model (LAM) for higher education that focuses on the dynamic interaction of stakeholders with their data supported by visual analytics, such as self‐organising maps, to generate conversations, shared inquiry and solution‐seeking. The model can be applied for other educational institutions interested in using learning analytics processes to support personalised learning and support services. Further work is testing its efficacy in increasing student retention rates.  相似文献   

14.
Augmented reality (AR) is currently considered as having potential for pedagogical applications. However, in science education, research regarding AR-aided learning is in its infancy. To understand how AR could help science learning, this review paper firstly has identified two major approaches of utilizing AR technology in science education, which are named as image-based AR and location-based AR. These approaches may result in different affordances for science learning. It is then found that students’ spatial ability, practical skills, and conceptual understanding are often afforded by image-based AR and location-based AR usually supports inquiry-based scientific activities. After examining what has been done in science learning with AR supports, several suggestions for future research are proposed. For example, more research is required to explore learning experience (e.g., motivation or cognitive load) and learner characteristics (e.g., spatial ability or perceived presence) involved in AR. Mixed methods of investigating learning process (e.g., a content analysis and a sequential analysis) and in-depth examination of user experience beyond usability (e.g., affective variables of esthetic pleasure or emotional fulfillment) should be considered. Combining image-based and location-based AR technology may bring new possibility for supporting science learning. Theories including mental models, spatial cognition, situated cognition, and social constructivist learning are suggested for the profitable uses of future AR research in science education.  相似文献   

15.
In this paper I will explain what I see as some of the core attributes of Communities of Innovation, or communities fostering collaborative creativity, and what we have learned from the research literature about each attribute. There is a critical need to design learning environments that foster creative thinking in students, particularly in the area of collaborative creativity. Many of the current problems and challenges graduates will face in society and industry are too large to be faced alone. However, the research and pedagogical understanding of how to develop skills in collaborative creativity is still underdeveloped. In seeking to understand what collaborative creativity would look like in education, I reviewed the literature on organizational and social creativity, along with social learning theory, to develop a framework of characteristics common to most environments that foster collaborative creativity in students (West, 2009). This framework describing Communities of Innovation explains some of the similar characteristics at the individual, group, and organizational levels of innovative communities.  相似文献   

16.
This study presents the outcomes of a semi-systematic literature review on the role of learning theory in multimodal learning analytics (MMLA) research. Based on previous systematic literature reviews in MMLA and an additional new search, 35 MMLA works were identified that use theory. The results show that MMLA studies do not always discuss their findings within an established theoretical framework. Most of the theory-driven MMLA studies are positioned in the cognitive and affective domains, and the three most frequently used theories are embodied cognition, cognitive load theory and control–value theory of achievement emotions. Often, the theories are only used to inform the study design, but there is a relationship between the most frequently used theories and the data modalities used to operationalize those theories. Although studies such as these are rare, the findings indicate that MMLA affordances can, indeed, lead to theoretical contributions to learning sciences. In this work, we discuss methods of accelerating theory-driven MMLA research and how this acceleration can extend or even create new theoretical knowledge.

Practitioner notes

What is already known about this topic
  • Multimodal learning analytics (MMLA) is an emerging field of research with inherent connections to advanced computational analyses of social phenomena.
  • MMLA can help us monitor learning activity at the micro-level and model cognitive, affective and social factors associated with learning using data from both physical and digital spaces.
  • MMLA provide new opportunities to support students' learning.
What this paper adds
  • Some MMLA works use theory, but, overall, the role of theory is currently limited.
  • The three theories dominating MMLA research are embodied cognition, control–value theory of achievement emotions and cognitive load theory.
  • Most of the theory-driven MMLA papers use theory ‘as is’ and do not consider the analytical and synthetic role of theory or aim to contribute to it.
Implications for practice and/or policy
  • If the ultimate goal of MMLA, and AI in Education in general, research is to understand and support human learning, these studies should be expected to align their findings (or not) with established relevant theories.
  • MMLA research is mature enough to contribute to learning theory, and more research should aim to do so.
  • MMLA researchers and practitioners, including technology designers, developers, educators and policy-makers, can use this review as an overview of the current state of theory-driven MMLA.
  相似文献   

17.
ABSTRACT

A common instructional practice in early childhood classrooms is the picturebook read aloud. The purpose of this investigation was to help preservice teachers learn to plan picturebook read alouds with the goal of helping children interpret the visual affordances of picturebooks, including visual elements (e.g., cclor, line) and peritextual components (e.g., title page, endpapers) as they engage in collaborative meaning making. In this qualitative study, the participants were 12 preservice teachers enrolled in an undergraduate children’s literature course. The findings presented here are focused on three participants that represented a range of growth and understandings about the picturebook format as well as growth and understandings about designing read aloud lessons. Findings indicate that while participants grew in their understandings of picturebook formats and in their ability to develop read aloud lesson plans with a visual focus, the rates and ways in which this occurred varied. Furthermore, the findings also suggest that crafting read alouds with a focus on visual affordances is a complex process and deserves careful attention in teacher preparation programs.  相似文献   

18.
This paper describes a technique for locating indicators of success within the data collected from complex learning environments, proposing an application of e‐research to access learner processes and measure and track group progress. The technique combines automated extraction of tense and modality via parts‐of‐speech tagging with a visualisation of the timing and speaker for each utterance developed to code and analyse learner discourse, exploiting the results of previous, non‐automated analyses for validation. The work is developed using a dataset of interactions within a multi‐user virtual environment and extended to a more complex dataset of synchronous chat texts during a collaborative design task. This methodology extends natural language processing into computer‐based collaboration contexts, discovering the linguistic micro‐events that construct the larger phases of successful design‐based learning.  相似文献   

19.
This review explores Jackson and Seiler’s “I am smart enough to study postsecondary science: A critical discourse analysis of latecomers’ identity construction in an online forum” by considering the analytic framework for figured worlds guiding this study. We consider the specific affordances of cultural production theory for examining how sociohistorical and cultural discourses of science as elite impact individuals at every level of education. We then extend this discussion by exploring how an informal learning space at a prestigious science museum was designed to explicitly tackle cultural discourses of science as elite that act as barriers to identification with science.  相似文献   

20.
An Amplified Mindset of Design (AMD) has emerged from recent research on emerging design practices, as designers are once again re‐inventing their identity to include an adaptability to uncertainty and paradox. However, this is not yet visible in what design education offers. As designers intervene in complex contexts and embrace participatory, collaborative and interdisciplinary practices informed by strong ethical and sustainability concerns, design education must adjust and expand its scope to include, for example, collaboration, cross‐cultural and interdisciplinary skills, and a way of being in the world through design. In this article, I argue for the formal introduction and exploration of social complexity in design education to assist the development of an AMD in design students. Boundaries, dependence on context, edge of chaos, emergence and organisation were identified as key qualities of complex systems to introduce to students. Embodiment and visualisation techniques were used as the most appropriate vehicles for such an endeavour. In this article, I discuss the results of a qualitative research informed by action research in which I explore ways of teaching complexity to design students. The inquiry was driven by the following core research question: How can complexity can be taught in design education using visual and embodiment methods to encourage the development of an Amplified Mindset of Design?  相似文献   

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