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Conferences, where to find us?

Soon the EARLI 2021 will be hosted virtually. 'The conference theme – Education and Citizenship: learning and Instruction and the Shaping of Futures – has a new resonance in the light of COVID-19.'

EARLI 2021 SCHEDULE

Final_EARLIE21_Schedule

View the schedule and see where you can find our ALL-group members!

Monday, 23rd of August 2021

Afbeelding1

Panel Discussion: Multimodal Measurement of SRL in Advanced Learning Technologies: 5 years of pioneering research.

Inge Molenaar, Radboud University, Netherlands; Roger Azevedo, University of Central Florida, United States; Sanna Järvelä, University of Oulu, Finland; Dragan Gasevic, Monash University, Australia; Maria Bannert, Technical University of Munich, Germany.

Time: 10:45 - 11:45

Location: Session Room 2 - Session A

erika inge

The process of learning scientific reasoning: a latent transition analysis.

Erika Schlatter, Radboud University, Netherlands; Inge Molenaar, Radboud University, Netherlands; Ard Lazonder, Radboud University, Netherlands.

In primary education children learn, among other things, scientific reasoning: the process of hypothesizing, experimenting, interpreting data and drawing conclusions. This important skill helps children learn science content and aids understanding of the world around them. Research has shown that the component scientific reasoning skills develop at a different pace and with substantial variation among same-age children. However, how these differences play out on the short term, for instance during a lesson series, is less well known. Latent transition analysis (LTA) can help shed light on such instant developmental differences and was used in the current study to analyze worksheets completed by 166 children during five hands-on science lessons. The study sought to answer two research questions: (1) can different proficiency profiles be found, and if so (2) how do children transition between these profiles? Four profiles were found in the data (see Figure 1): high achievers (high scores on all subskills), low achievers (low scores on all subskills), experimenters (low scores on all subskills except experimenting), and theorists (high scores on all subskills except experimenting). Children transitioned between these profiles regularly (see Figure 2), in particular during the first half of the lesson series. Extreme transitions (between low and high achievers, or between theorists and experimenters) gradually diminished, and transitions from profiles with high experimenting scores to profiles with low experimenting scores were rare. Knowing these individual differences in the development of scientific reasoning helps us further understand its development, and can help teachers provide personalized instruction.

Time: 10:45 - 11:45

Location: Session Room 4 - Session A

Tuesday, 24th of August 2021

rick inge

Real time measuring of individual learners’ self regulation during learning.

Rick Dijkstra, Radboud University, Netherlands; Inge Molenaar, Radboud University, Netherlands; Max Hinne, Radboud University, Netherlands.

Time: 18:45 - 19:45

Location: Session Room 6 - Session K

Wednesday, 25th of August 2021

jolique inge

Reading Strategies and Patterns during Task-Oriented Reading.

Jolique Kielstra, Radboud University, Netherlands; Inge Molenaar, Radboud University, Netherlands; Roel van Steensel, Erasmus University, Netherlands; Ludo Verhoeven, Radboud University, Netherlands.

Task-oriented reading involves reading with the purpose of processing information for the execution of a specific task. Thus, students need to decide what to read and how to process the text. These decisions require students to regulate their strategy use during reading. In this study, we examined reading patterns of 44 vocational students, while they were executing a task. These tasks differ in form and complexity, resulting in differences in how students read the text accompanying the task. Logdata from students of these different reading processes was transformed into 1091 reading graphs to investigate students reading patterns from a macro-level perspective. At the same time, the occurrence of individual reading strategies, such as re-reading and number of search decisions, are also identifiable within these patterns. We found three distinguishable macro-level reading patterns, a search reading pattern, a targeted reading pattern and an intensive reading pattern. This provides insight into how students reading process differs while they are executing tasks, which can be used for future feedback purposes.

Time: 12:00 - 13.00

Location: Session Room 17 - Session M

joep

The Association of Offline and Online Inquiry Skills with Conceptual and Procedural Knowledge.

Joep van der Graaf, Radboud University, Netherlands.

Inquiry-based learning fosters acquisition of domain knowledge and inquiry skills. While the bidirectional relationship between inquiry skills and domain knowledge has been established, more research is needed to compare offline with online inquiry measures, and conceptual with procedural knowledge. Therefore, the present study aimed to provide more insight into the bidirectional relationship between knowledge and inquiry. A digital inquiry-based lesson about gears was used. Offline inquiry skills (hypothesis generation/evidence evaluation and experimentation) were assessed with a questionnaire. Conceptual and procedural knowledge about gears were assessed before and after the inquiry-based lesson using questionnaires. During the inquiry-based lesson, online measures of inquiry (hypothesis generation and experimentation) were collected using log data. Results showed that offline and online measures of inquiry skills were partially related. Prior procedural knowledge was associated with online hypothesis generation and experimentation. Finally, online hypothesis generation related to learning of procedural knowledge of gears’ turning speed and online experimentation to learning of procedural knowledge of gears’ turning direction. These results align with previous research, and add that online measures of inquiry-based learning appeared to be better explain learning of domain knowledge than offline measures, and that procedural and conceptual knowledge might contribute differently to inquiry-based learning.

Time: 15:45 - 16.45

Location: Session Room 6 - Session N

anne

Building blocks for higher education teachers’ professional development aimed at innovation with IT.

Marlies ter Beek, University of Twente, Netherlands; Kim Schildkamp, University of Twente, Netherlands; Dorien Hopster-den Otter, University of Twente, Netherlands; Anne Horvers, Radboud University, Netherlands.

Time: 17:30 - 18:30

Location: Session Room 16 - Session O

inge anne rick

What can enactment of control during learning tell about students’ motivation?

Inge Molenaar, Radboud University, Netherlands; Anne Horvers, Radboud University, Netherlands; Rick Dijkstra, Radboud University, Netherlands.

Time: 17:30 - 18:30

Location: Session Room 17 - Session O

anne inge rick

Young learners' use of increased autonomy and personalized visualizations to regulate learning.

Anne Horvers, Radboud University, Netherlands; Inge Molenaar, Radboud University, Netherlands; Rick Dijkstra, Radboud University, Netherlands.

Time: 17:30 - 18:30

Location: Session Room 10 - Session O

Thursday, 26th of August 2021

carolien

Impact of audio-support on reading strategy, time, and performance in students with dyslexia.

Carolien A. N. Knoop-van Campen, Radboud University, Netherlands; Danique ter Doest, Radboud University, Netherlands; Ludo Verhoeven, Radboud University, Netherlands; Eliane Segers, Radboud University, Netherlands.

The use of adequate reading strategies is important to read efficiently. Students with dyslexia, not only read slower and less accurately, they also use fewer reading strategies. To compensate for their reading problems, they often receive audio-support via narration of the written text. However, audio-support linearly guides readers from beginning to end through a text, possibly hindering the use of reading strategies, and negatively impacting reading time and comprehension. Therefore, we examined to what extent audio-support in reading comprehension affects reading strategies, times and performance in 21 secondary school students with dyslexia and 22 typically developing controls. Participants were provided with three types of assignments (summarizing, open-ended questions, statement questions) in each condition (written text with and without audio-support). A SMI RED-500 eye-tracker captured eye-movements during reading. The standard deviation of the weighted fixation duration times of the text-AOIs was considered indicative of the disparity of readers’ attention within the text. Based on an experts’ cut-off point and hand-coded validation, these scores visualized whether students used the intensive reading strategy (reading whole text) or selective reading strategy (focusing on part of the text). In open-ended assignments students with dyslexia divided their attention more over the whole text instead of focusing on one specific part when audio was added. In addition, audio-support increased reading time in students with and without dyslexia in most tasks, while in neither of the task’s audio-support affected performance. It is concluded that audio-support impacts reading strategy in students with dyslexia and reading time in all students.

Time: 12:00 - 13:00

Location: Session Room 8 - Session R

joep

New Ways of Measuring, Analysing and Scaffolding Self-Regulated Learning.

Joep van der Graaf, Radboud University, Netherlands; Philip Winne, Simon Fraser University, Canada

New ways of measuring and analysing Self-Regulated Learning (SRL) are rapidly emerging. This has important implications for theoretical frameworks of SRL, methodological approaches, and for current educational practices. The first aim of this symposium is to present and discuss new approaches to measurement and analysis of SRL. The second aim is to provide suggestions on the design of educational materials that provide additional insights into students’ learning processes and support their SRL. The presenters are a group of international researchers, who have a strong interest in learning analytics and/or SRL. The presentations are incrementally ordered, moving from measurement and analysis of SRL (1, 2) to learning outcomes (3) and ending with a digital learning tool (4). The four presentations revolve around the following main questions: a) How can multimodal data improve the granularity of measurement of SRL? b) How does SRL unfold in high versus low performing students? c) How do SRL activities relate to different learning outcomes? And d) How can we support students by visualising their SRL process? By addressing these questions, this symposium provides suggestions for theory and methodological development as well as educational practice.

Time: 15:45 - 16:45

Location: Session Room 5 - Session T

joep inge

Improving the granularity for the measurement of self-regulated learning using multi-channel data.

Yizhou Fan, The University of Edinburgh, United Kingdom; Lyn Lim, Technical University of Munich, Germany; Joep van der Graaf, Radboud University, Netherlands; Jonathan Kilgour, The University of Edinburgh, United Kingdom; Johanna Moore, The University of Edinburgh, United Kingdom; Dragan Gasevic, Monash University, Australia; Maria Bannert, Technical University of Munich, Germany; Inge Molenaar, Radboud University, Netherlands.

In recent years, unobtrusive measures of self-regulated learning (SRL) processes based on log data recorded by digital learning environments have attracted increasing attention. However, researchers have also recognised that simple navigational log data or time spent on pages are often not fine-grained enough to study complex SRL processes. Recent advances in data-capturing technologies enabled researchers to go beyond simple navigational logs to measure SRL processes with multi-channel data. Though, to what extent can the addition of peripheral and eye-tracking data with navigational data improve the granularity of measurement of SRL are key questions that require further investigation. Hence, we conducted a study that aimed to address this problem by enhancing navigational log data with peripheral and eye-tracking data. Based on the measurement protocol proposed in this study, we were able to compare the process models of SRL of n=25 students across different data channels. The results revealed that by adding new data channels, we improved the capture of learning actions and detected SRL processes while enhancing the granularity of the measurement. In addition, we also concluded that eye-tracking data is valuable for measuring and extracting SRL processes, and it should receive more attention in the future.

Time: 15:45 - 16:45

Location: Session Room 5 - Session T

joep inge

Understanding Self-Regulated Learning Processes through Process Mining.

Lyn Lim, Technical University of Munich, Germany; Maria Bannert, Technical University of Munich, Germany; Joep van der Graaf, Radboud University, Netherlands; Yizhou Fan, The University of Edinburgh, United Kingdom; Jonathan Kilgour, The University of Edinburgh, United Kingdom;  Inge Molenaar, Radboud University, Netherlands; Johanna Moore, The University of Edinburgh, United Kingdom; Dragan Gasevic, Monash University, Australia.

Self-regulated learning (SRL) is related to better learning outcomes and observation of SRL using think aloud data has been shown to be more insightful in determining SRL activities and predicting students’ learning achievements than self-reports. Educational process mining, moreover with think aloud data, enables a deeper understanding and a more fine-grained analysis of SRL processes. This study based on a pre-post design aimed to investigate how students differ in SRL learning processes and how this affects learning performance. There were 32 university students who participated in the study to learn about the theme, “Artificial Intelligence in Education”, and they had to write an essay in a digital learning environment within a 45-minute learning session while thinking aloud. The results showed that there is a significant learning gain in the knowledge test. Besides, the top performers showed more metacognitive and cognitive activities during learning. Furthermore, process mining using HeuristicMiner algorithm based on post hoc coded think aloud protocols examined differences in process structures of SRL for the high and low performers. In general, comparing resulting process mining models with prior process mining models will help to better generalize findings of prior research.

Time: 15:45 - 16:45

Location: Session Room 5 - Session T

joep inge

How Self-Regulated Learning Affects Different Learning Outcomes.

Joep van der Graaf, Radboud University, Netherlands; Lyn Lim, Technical University of Munich, Germany; Yizhou Fan, The University of Edinburgh, United Kingdom; Jonathan Kilgour, The University of Edinburgh, United Kingdom; Johanna Moore, The University of Edinburgh, United Kingdom; Dragan Gasevic, Monash University, Australia; Maria Bannert, Technical University of Munich, Germany; Inge Molenaar, Radboud University, Netherlands.

Self-regulated learning (SRL) fosters transfer, but effects on other learning outcomes, such as domain knowledge are mixed. SRL potentially has a differential impact on learning outcomes with different characteristics, deep vs surface knowledge, and independent vs connected concepts. Therefore, we assessed how surface knowledge measured with a domain test (independent), and a concept map (connected) and deep knowledge measured with a transfer test (independent) and an essay (connected) are associated to SRL activities during learning and to prior metacognitive knowledge. Forty-five university students performed a 45-minute problem-solving task integrating three topics into a vision on future of education. SRL activities were measured using think aloud. Results revealed learning occurred. Surface knowledge measures, independent and connected concepts, were related to each other and associated with low cognitive activities during learning. Deep knowledge of independent concepts was associated with low cognitive processes, while deep knowledge of connected concepts was associated with a mixture of low and high cognitive processes. In addition, we found that prior metacognitive knowledge was associated with deep knowledge of independent concepts. To conclude, taking the level and structure of knowledge into account helps to specify effects of SRL processes on learning outcomes.

Time: 15:45 - 16:45

Location: Session Room 5 - Session T

joep inge

Visualising student’s learning strategies in online learning to support self-regulation.

Shaveen Singh, Monash University, Australia; Mladen Rakovic, Monash University, Australia, Yizhou Fan, The University of Edinburgh, United Kingdom; Lyn Lim, Technical University of Munich, Germany; Joep van der Graaf, Radboud University, Netherlands; Jonathan Kilgour, The University of Edinburgh, United Kingdom; Inge Molenaar, Radboud University, Netherlands; Johanna Moore, The University of Edinburgh, United Kingdom; Maria Bannert, Technical University of Munich, Germany; Dragan Gasevic, Monash University, Australia.

Visualisations provide an effective way for learners to gain insight into their learning process which, in turn, may promote their self-regulated learning. Yet few learner-facing visualisations have been developed to support learners’ self-regulation. To this purpose, we propose a collection of personalised, theory-based and empirically driven visual interfaces. We harnessed trace data from multiple channels to generate clear and actionable recommendations for learners to improve their regulation. Guided by a quasi-experimental study in an university context (n=25), we investigated the student’s critical learning processes in SRL, such as, planning, content consumption, working on task, monitoring and evaluation. In the presentation, we describe the learning environment to collect data about those processes, and suggest visualizations that rely upon these data sources. In an ongoing study, we will prompt learners to engage in metacognitive monitoring of their learning using visualisations to support their regulation and learning.

Time: 15:45 - 16:45

Location: Session Room 5 - Session T

anne inge

Exploring students’ emotions during learning with adaptive learning technology: a multimodal approach.

Anne Horvers, Radboud University, Netherlands; Inge Molenaar, Radboud University, Netherlands; Tibor Bosse, Radboud University, Netherlands; Ard Lazonder, Radboud University, Netherlands.

Time: 17:30 - 18:30

Location: Session Room 4 - Session U

inge

Leveraging SRL research into intelligent learning technologies

Sanna Järvelä, University of Oulu, Finland; Inge Molenaar, Radboud University, Netherlands; Arthur Graesser, University of Memphis, United States.

Time: 17:30 - 18:30

Location: Session Room 3 - Session U

joep inge

Multimodal Data Analysis of Student’s own Regulation Activities to Advance Personalized Scaffolds.

Maria Bannert, Technical University of Munich, Germany; Lyn Lim, Technical University of Munich, Germany; Joep van der Graaf, Radboud University, Netherlands; Yizhou Fan, The University of Edinburgh, United Kingdom; Jonathan Kilgour, The University of Edinburgh, United Kingdom; Inge Molenaar, Radboud University, Netherlands; Johanna Moore, The University of Edinburgh, United Kingdom; Dragan Gasevic, Monash University, Australia.

Time: 17:30 - 18:30

Location: Session Room 3 - Session U

inge

Towards Hybrid Human-AI Regulation: Supporting Young learners’ Self-regulated Learning.

Inge Molenaar, Radboud University, Netherlands.

Time: 17:30 - 18:30

Location: Session Room 3 - Session U

ina inge

What teachers think and do: adaptive teaching in blended classrooms

Ina Cijvat, Radboud University, Netherlands; Eddie Denessen, Radboud University, Netherlands; Inge Molenaar, Radboud University, Netherlands; Peter Sleegers, BMC Groep, Netherlands

As primary school teachers are dealing with increasing diversity of students’ cognitive ability, there is a growing need for adaptive teaching practices. Educational technologies are proposed as a possible means to support adaptivity in classrooms. This novel context requires that teachers redevelop their adaptive teaching skills. At the heart of adaptive teaching is the ability to adjust to the needs of individual students. In this study we investigate moments of adaptation which are coded as routine or (thoughtful) change depending on the teachers’ reflections. An in-depth multiple case study methodology was applied with twelve teachers (students 8 to 12 years) in three primary schools. Teachers' moments of adaptation in adaptive teaching were analysed. Teachers relatively often adjusted the instruction to their students, often based on their own observations of student learning, sometimes also based on the data on student learning provided by the educational technology. Preset decisions (i.e. decisions anticipated on in the lesson preparation phase) were proportionally more common at routine moments of adaptivity, while flexible (i.e. unanticipated) decisions were slightly more common during moments of (thoughtful) change. Also, teachers used the educational technology more frequently during moments of (thoughtful) change.

Time: 18:45 - 19:45

Location: Session Room 9 - Session V

Friday, 27th of August 2021

erika inge

Effects of micro- and macro-adaptive instruction on children’s learning of scientific reasoning.

Erika Schlatter, Radboud University, Netherlands; Inge Molenaar, Radboud University, Netherlands; Ard Lazonder, Radboud University, Netherlands.

Scientific reasoning is an important skill that helps children understand the world around them. Teaching scientific reasoning starts in primary school and can be challenging: not all component scientific reasoning skills develop at the same age and not all children learn these skills at the same pace. A differentiated teaching approach thus seems called for, but few guidelines for adaptive science instruction exist. The current study sought to aid the development of such guidelines by comparing two types of adaptive instruction to a non-adaptive control condition. Over the course of four lessons, children in the control condition (n=49) practiced scientific reasoning skills with the help of worksheets with light support. Children in the two adaptive instruction conditions received worksheets with more specific support that was either based on their standardized test scores of reading comprehension and mathematical skillfulness (macro-adaptive condition; n=58) or their performance in the previous lesson (micro-adaptive condition; n=46). Thus, the two adaptive conditions differed regarding the information used to assign children to a level of instruction, as well as the frequency with which this information was updated. Analysis of children’s pre- and posttest scores showed improved scientific reasoning ability in all three conditions, but no effect of condition was found. Further analysis of children’s worksheets is ongoing and will reveal whether the adaptive instructions had a differential effect on children’s scientific reasoning during the lessons.

Time: 09:00 - 10:00

Location: Session Room 15 - Session W