Abstract.
In this keynote lecture I will present my view on how important humans are – and will increasingly be – for guiding future learning and professional development. Given the theme of this SIG14 meeting 'Learning On-the-Go: Understanding the Dynamics of Continuous Professional Development in a Tech-Driven World' I thus decided to focus on ‘Human-Driven Learning and Development’.

In doing this, I will draw some parallels with technology-enhanced learning and instruction in higher education settings, focusing on challenges for developing online and blended learning environments and course design. I will make the point that we have been moving to a digital first type of education that is still human centered.

Both what technologies can bring to the table with regard to learning and professional development, as well as what human facilitators can bring to the table will be discussed, as well as competences needed for facilitating learning and professional development in an increasing digital world.

Based on PIAAC (Programme for the International Assessment of Adult Competencies, OECD) and related data I will also focus on differences regarding shorter and longer educated people, how they look at learning, and how we may need human-driven learning and professional development to ensure a broad spectrum of future opportunities for learning and development for all.

Conference.
EARLI SIG 14 Conference 2024 'Learning On-the-Go: Understanding the Dynamics of Continuous Professional Development in a Tech-Driven World'. https://www.jyu.fi/en/events/earli-sig14-conference-2024

Special Interest Group (SIG) 14 of the European Association for Research on Learning and Instruction (EARLI) is focusing on Learning and professional development. It brings together researchers who study work and education as contexts for professional learning.

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Impression.

Abstract.
The design of blended learning environments brings with it four key challenges: (1) incorporating flexibility, (2) stimulating interaction, (3) facilitating students’ learning processes, and (4) fostering an affective learning climate. Seeing that attempts to resolve these challenges are fragmented across the literature, a systematic review was performed. Starting from 640 sources, 20 studies on the design of blended learning environments were selected through a staged procedure based on the guidelines of the PRISMA statement, using predefined selection criteria. For each study, the instructional activities for dealing with these four challenges were analyzed by two coders. The results show that few studies offer learners control over the realization of the blend. Social interaction is generally stimulated through introductory face-to-face meetings, while personalization and monitoring of students’ learning progress is commonly organized through online instructional activities. Finally, little attention is paid to instructional activities that foster an affective learning climate.

Keywords.
Instructional activities; blended learning; educational technology; course design

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Abstract.
Background: This case reports on a teacher education course that aimed to support adult learners with a vocational education background to accomplish open-ended tasks. Conjecture mapping was used to identify the most salient design features, and to test if, how, and why these course features supported learners. Methods: Inspired by ethnographic approaches, sustained engagement and multiple data sources were used to explain the effects of the course design on participants’ behavior and perceptions: student and teacher interviews, observations, and artifacts. Findings: The results reveal that almost all of the proposed design features stimulated the participants toward the intended enactment processes, which in turn yielded the intended learning outcomes. For instance, worked examples (i.e., design feature) not only engendered the production of artifacts that meet high standards (i.e., enactment process) because they clarify the task requirements, but also fostered a safe structure (i.e., enactment process) by providing an overall picture of the task. Contribution: The conjecture map resulting from this study provides a theoretical frame to describe, explain, and predict how specific course design features support vocationally educated adult learners (VEAL) in open-ended tasks, and assists those who aim to implement open-ended tasks in similar contexts.

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Abstract.
As a growing number of educational institutions are offering online programs, teachers need to be competent in this new way of teaching. This is especially the case for synchronous online learning through videoconferencing technology, an emergent and so far understudied form of online education. Based on a systematic literature review of 30 studies, this study identifies 24 competence clusters, which can be grouped into 5 teacher roles associated with synchronous online teaching through videoconferencing: the instructional, managerial, technical, communicational, and social role. This framework can act as a starting point for future research on this understudied topic and can also provide directions to support teachers’ professionalization and practice.

Keywords.
Review study; Synchronous online videoconferencing teaching; Teacher roles; Teacher competences

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Abstract.
The shift to a knowledge society has transformed the way we live and work, which is especially challenging to adults with low education levels. Adult education could be the answer, but low-educated adults participate least in adult education. The present study uses data from the Programme for the International Assessment of Adult Competencies to investigate participation needs and barriers of low-, medium- and high-educated adults across 15 European countries (N = 20,593). Descriptives show that low-educated adults report the lowest need for training to exercise their job and indicate to be the least prevented from taking more training because of experienced barriers. We then analysed which barriers non-participating and participating adults were referring to. While medium- and high-educated non-participants indicate being prevented because of work and family responsibilities, low-educated non-participants chose family responsibilities but mainly and remarkably the option ‘other’ as their most important barrier. Contrary to medium- and high-educated adults, low-educated adults’ most important barrier could not be defined. A possible explanation is that they experience more dispositional barriers (such as bad memories of education or low self-esteem), which were not included in the list. Our results point to the importance of targeting low-educated adults in participation research.

Keywords.
Barriers, PIAAC, adult education, low-educated adults, Europe

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Abstract.
Despite the attention devoted to situational and institutional barriers in studying participation in adult education, psychosocial barriers are often overlooked in research. However, low-educated, and non-participating adults are more likely to experience them. In this study, we examine low-educated, both participating and non-participating, adults’ psychosocial views on learning. We interviewed 15 adults by using vignettes to elicit discussion on a delicate and difficult to interview theme and carried out a qualitative content analysis. Our findings demonstrate that adults point to situational barriers for not participating and, contrary to what we anticipated, have positive general attitudes towards learning. However, there are several prerequisites to having this attitude. For instance, learning has to be useful, a learning trigger is needed, spare hours should not be devoted, and there should be no exams or tests. As a result, our research demonstrates the complex nature of perceived ‘situational’ barriers, which frequently pertain to psychosocial stances.

Keywords.
Barriers, PIAAC, adult education, low-educated adults, Europe

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Abstract.
In an authentic flight simulator, the instructor is traditionally located behind the learner and is thus unable to observe the pilot's visual attention (i.e. gaze behaviour). The focus of this article is visual attention in relation to pilots' professional learning in an Airbus A320 Full Flight Simulator. For this purpose, we measured and analysed pilots' visual scanning behaviour during flight simulation-based training. Eye-tracking data were collected from the participants (N = 15 pilots in training) to objectively and non-intrusively study their visual attention behaviour. First, we derived and compared the visual scanning patterns. The descriptive statistics revealed the pilots' visual scanning paths and whether they followed the expected flight protocol. Second, we developed a procedure to automate the analysis. Specifically, a Hidden Markov model (HMM) was used to automatically capture the actual phases of pilots' visual scanning. The advantage of this technique is that it is not bound to manual assessment based on graphs or descriptive data. In addition, different scanning patterns can be revealed in authentic learning situations where gaze behaviour is not known in advance. Our results illustrate that HMM can provide a complementary approach to descriptive statistics. Implications for future research are discussed, including how artificial intelligence in education could benefit from the HMM approach.

Keywords.
SIMULATION, TECHNOLOGY, STRATEGIES, ATTENTION, AWARENESS, PATTERNS, Adult learning, Simulations, Applications in subject areas, Eye tracking, Hidden Markov model

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Abstract.
We present a privacy-friendly early-detection framework to identify students at risk of failing in introductory programming courses at university. The framework was validated for two different courses with annual editions taken by higher education students ( N = 2 080) and was found to be highly accurate and robust against variation in course structures, teaching and learning styles, programming exercises and classification algorithms. By using interpretable machine learning techniques, the framework also provides insight into what aspects of practising programming skills promote or inhibit learning or have no or minor effect on the learning process. Findings showed that the framework was capable of predicting students’ future success already early on in the semester.

Keywords.
Computer Science Applications, Education, educational data mining, pass, fail prediction, intelligent tutoring systems, computer programming, computer science education

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Abstract.
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first student pass–fail prediction approach proposed by Van Petegem and colleagues (2022) in a different CS1 course. Using student submission and self-report data, we investigated the reproducibility of the original approach, the effect of adding self-reports to the model, and the interpretability of the model features. The results showed that the original approach for student dropout prediction could be successfully reproduced in a different course context and that adding self-report data to the prediction model improved accuracy for the first four weeks. We also identified relevant features associated with dropout in the CS1 course, such as timely submission of tasks and iterative problem solving. When analyzing student behaviour, submission data and self-report data were found to complement each other. The results highlight the importance of transparency and generalizability in learning analytics and the need for future research to identify other factors beyond self-reported aptitude measures and student behaviour that can enhance dropout prediction.

Keywords.
Computer Science Applications, Education, Predictive learning analytics, CS1, retention, privacy, self-report data, trace data

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