1,721,001 research outputs found
Measuring affective and motivational states as conditions for cognitive and metacognitive processing in self-regulated learning
Get PDFEven though the engagement in self-regulated learning (SRL) has been shown to boost academic performance, SRL skills of many learners remain underdeveloped. They often struggle to productively navigate multiple cognitive, affective, metacognitive and motivational (CAMM) processes in SRL. To provide learners with the required SRL support, it is essential to understand how learners enact CAMM processes as they study. More research is needed to advance the measurement of affective and motivational processes within SRL, and investigate how these processes influence learners' cognition and metacognition. With this in mind, we conducted a lab study involving 22 university students who worked on a 45-minute reading and writing task in digital learning environment. We used a wearable electroencephalogram device to record learner academic emotional and motivational states, and digital trace data to record learner cognitive and metacognitive processes. We harnessed time series prediction and explainable artificial intelligence methods to examine how learner's emotional and motivational states influence their choice of cognitive and metacognitive processes. Our results indicate that emotional and motivational states can predict learners' use of low cognitive, high cognitive and metacognitive processes with considerable classification accuracy (F1 > 0.73), and that higher values of interest, engagement and excitement promote cognitive processing.</p
A tutorial on data storytelling techniques for learning analytics dashboards
Get PDFSupporting educational stakeholders to interpret dashboards and visualizations poses critical design challenges that may often be trivialized. Teachers’ and students' interpretation of visualized data is essentially the construction of a narrative about the learning process. Applying data storytelling techniques to design these visualizations can support the generation of insights derived from educational data by aligning the intended learning design, goals and outcomes with visual elements. The aim of this tutorial is to introduce participants to embrace data storytelling techniques into the design of visualizations and dashboards that can communicate meaningful insights
Analytics-based approach to the study of learning networks in digital education settings
Get PDFInvestigating howgroups communicate, build knowledge and expertise, reach consensus or collaboratively
solve complex problems, became one of the main foci of contemporary research in learning and
social sciences. Emerging models of communication and empowerment of networks as a form of social
organization further reshaped practice and pedagogy of online education, bringing research on learning
networks into the mainstream of educational and social science research. In such conditions, massive
open online courses (MOOCs) emerged as one of the promising approaches to facilitating learning
in networked settings and shifting education towards more open and lifelong learning. Nevertheless,
this most recent educational turn highlights the importance of understanding social and technological
(i.e., material) factors as mutually interdependent, challenging the existing forms of pedagogy and
practice of assessment for learning in online environments.
On the other hand, the main focus of the contemporary research on networked learning is primarily
oriented towards retrospective analysis of learning networks and informing design of future
tasks and recommendations for learning. Although providing invaluable insights for understanding
learning in networked settings, the nature of commonly applied approaches does not necessarily allow
for providing means for understanding learning as it unfolds. In that sense, learning analytics, as
a multidisciplinary research field, presents a complementary research strand to the contemporary research
on learning networks. Providing theory-driven and analytics-based methods that would allow
for comprehensive assessment of complex learning skills, learning analytics positions itself either as
the end point or a part of the pedagogy of learning in networked settings.
The thesis contributes to the development of learning analytics-based research in studying learning
networks that emerge fromthe context of learning with MOOCs. Being rooted in the well-established
evidence-centered design assessment framework, the thesis develops a conceptual analytics-based
model that provides means for understanding learning networks from both individual and network
levels. The proposed model provides a theory-driven conceptualization of the main constructs, along
with their mutual relationships, necessary for studying learning networks. Specifically, to provide
comprehensive understanding of learning networks, it is necessary to account for structure of learner
interactions, discourse generated in the learning process, and dynamics of structural and discourse
properties. These three elements – structure, discourse, and dynamics – should be observed as mutually
dependent, taking into account learners’ personal interests, motivation, behavior, and contextual
factors that determine the environment in which a specific learning network develops. The thesis also
offers an operationalization of the constructs identified in the model with the aim at providing learning analytics-methods for the implementation of assessment for learning. In so doing, I offered a redefinition
of the existing educational framework that defines learner engagement in order to account
for specific aspects of learning networks emerging from learning with MOOCs. Finally, throughout
the empirical work presented in five peer-reviewed studies, the thesis provides an evaluation of the
proposed model and introduces novel learning analytics methods that provide different perspectives
for understanding learning networks. The empirical work also provides significant theoretical and
methodological contributions for research and practice in the context of learning networks emerging
from learning with MOOCs
Dichotomous views of automation in feedback practice
Get PDFThis poster describes a pilot study at a Brazilian university, which involves a survey that seeks to explore elements of feedback that are perceived as important by students, including the role of automation. The purpose is to inform the implementation of a learning analytics-based feedback tool, OnTask. The results show that the most valued elements of feedback are the identification of attainment gaps and the relational nature of feedback. These views are also reflected in student concerns around automation, i.e., the loss of teacher-student interactions despite their positive views on efficiency and timeliness. The study concludes with the need to highlight the human inputs in the adoption of OnTask attend to the varying feedback literacy among learners
A network analytic approach to integrating multiple quality measures for asynchronous online discussions
Get PDFAsynchronous online discussions within a community of learners can improve learning outcomes through social knowledge construction, but the depth and quality of student contributions often varies widely. Approaches to assessing critical discourse typically use content analysis to identify indicators that correspond to framework constructs, that in turn serve as measures of depth and quality. Often only a single construct is addressed for performing content analysis in the literature, although recent work has used both social presence and cognitive presence constructs from the Community of Inquiry (CoI) framework. Nevertheless, there is no effective, commonly used, analytic approach to combining insights from multiple perspectives about quality and depth of online discussions. This paper addresses the gap by proposing the combined use of cognitive engagement (the ICAP framework) and cognitive presence (CoI); and by proposing a network analytic approach that quantifies the associations between the two frameworks and measures the moderation effects of two instructional interventions on those associations. The present study found that these associations were moderated by one intervention but not the other; and that messages labelled with the most common phase of cognitive presence could be usefully assigned to smaller meaningful subgroups by also considering the mode of cognitive engagement
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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