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In the field of aviation, air traffic controllers must be able to adapt to and act upon continuing changes in a highly advanced technological work environ- ment. This position paper claims that explicit training of self-directed learning skills (i.e. the ability to: formulate own learning needs, set own learning goals, and identify learning tasks that help to achieve personal learning goals) is important for future professionals in aviation. In this paper, we present an adaptive training system in which the system and trainee share control over learning task selection and which can help trainees to develop their self- directed learning skills.

Self-regulated learning (SRL) skills are especially important in professions where the half-life of initial training and education is short and where knowledge and skill obsolescence is quick. An example of just such a profession can be found in the constantly evolving field of Air Traffic Control (ATC), and thus SRL skills are essential for ATC trainees. If Air Traffic Controllers are to become and remain competent we must gain insight into how ATC trainees regulate their learning during task performance, how the acquisition of SRL skills can be stimulated, and thus how this can be measured. This study examines the use of cued retrospective reporting to measure learners’ SRL activities during the execution of complex ATC tasks. Results show that cued retrospective reporting is a workable method for measuring an extensive collection of regulation activities of ATC trainees. Further, relation between ATC task performances and SRL activities and other relating learner characteristics (i.e. Self-directed learning skills and the learners self-efficacy beliefs) were found.

Zowel Self-efficacy als Self-directed learing zijn bekende leerling-eigenschappen ter ondersteuning voor succesvol leren. Vooral in het aanleren van complexe vaardigheden in een domein zoals luchtverkeersleiding, is het meten van deze leerling-eigenschappen van belang om ontwikkeling van deze leerling-eigenschappen te kunnen monitoren en zo het aanleren van de domeinspecifieke vaardigheden te ondersteunen. Goede vragenlijsten om dit te meten zijn de STPQ en PRO-SDLS. Beide lijsten zijn echter in het Engels. In deze studie bespreken we het proces en de uitkomsten van vertalen en valideren van de Nederlandse vertalingen van deze twee vragenlijsten. Voor de validatie van de Nederlandstalige STPQ deden 80 selectiekandidaten van luchtverkeersleiding Nederland vrijwillig mee. Door middel van factoranalyse en betrouwbaarheidsanalyse zijn twee schalen bepaald: 1: Self-efficacy voor taakprestatie, 2: Self-efficacy voor leren. Voor de validatie van de Nederlandstalige PRO-SDL deden 158 leerlingen 2e-jaars Aviation studies van de Hogeschool van Amsterdam vrijwillig mee. Door middel van factoranalyse en betrouwbaarheidsanalyse zijn ook hier twee schalen bepaald: 1: Zelfsturing, 2: Initiatief nemen.

Future changes in aviation technologies require Air-traffic Control (ATC) professionals to be able to adapt to these coming changes in their profession. To be able to adapt to new situations professionals must be able to define learning needs, set learning goals and identify human and material resources (e.g. task selection) to fulfil these needs. These skills are called self-directed learning (SDL) skills Knowles (1975). As a consequence, in ATC training, SDL skills should be developed in an adaptive training system (Van Meeuwen, Brand-Gruwel, Van Merriënboer, & De Bock, 2009). However, in order to self-direct learning, insight in to past performance is necessary. It requires a self-assessment from a present situation. Self-assessment can be seen as one of the self-regulated learning (SRL) skills (Zimmerman, 1990). This leaves the following research question to answer: Can we measure the learners SRL skills without disturbing task performance and is there a relation between learners’ SRL-skills during task performance and the quality of their SDL-skills?

Air Traffic Control (ATC) is a cognitive complex job. To access Air Traffic Control (ATC) training, a selection procedure takes place. This selection increases the chances of trainees reaching the high standards at the end of the training. Nevertheless, still a large number of trainees drops out. To improve trainees learning skills, in this study indicators for successful learning in ATC training have been examined; based on focus group meetings with ATC training experts, ATC trainers, and ATC trainees, indicators for successful learning were formulated. Results show that both the experts and trainers identify setting own learning goals, identifying own human and material resources, and self-efficacy as important indicators for successful learning. The trainees, however, identified the ability to adjust task performance and the orientation on task performance as important indicators for successful learning in ATC training. Overall, a significant agreement was found between the rankings of all three focus groups. This resulted in a ranking of most important indicators in ATC training by each group. The ranking of the experts and trainers correlated significantly, whereas no correlation was found between the trainee group and any of the other groups. Differences and similarities in agreement between groups are discussed. In addition guidelines for instructional design are formulated in which optimal trainee involvement in individual ATC competence development is discussed.

Successful training of air traffic controllers includes both the development of domain specific competences (e.g., visual problem solving skills) and the acquisition of self-regulation skills. The aim of this dissertation is to increase understanding of the complexity of the ATC domain (i.e., specifically visual problem solving) and to design and test a learning environment which integrates the development of self-regulation skills in the domain-specific training. To answer the aforementioned research questions, the studies presented in this dissertation take three approaches. The first approach focuses on the complexity of the ATC domain by elaborating on required visual expertise and specifically on the underlying visual problem solving strategies. The second approach focuses on self-regulation, and specifically on how SRL skills, SDL skills and self-efficacy mutually interact and what their importance is for successful ATC-training. The third approach focuses on a training design which integrates the development of the students’ regulation skills with the development of domain specific ATC-competences. The training design includes shared control in the environment between the system (i.e., the trainer and the environment) and the learner. In this third approach, a practical study is also presented which deals with the implications of parts of such training design on successful training in ATC and on the development of self-regulation skills. The four subsequent chapters aim at answering the four research questions, respectively. Chapter 2 presents a study which matches strategies for visual problem solving with performance of novices, intermediates and experts in the ATC-domain. Eye-tracking is used to investigate eye-movements of respondents at these three levels of expertise. The use of visual problem solving strategies such as means-end analysis, information reduction and chunking are mapped out for novices, intermediates and experts. Also the performance similarity between participants is investigated to gain insight in the influence of specific strategy use and expertise on the diversity of traffic conflict solutions found. The chapter discusses implications of differences of solution similarity and visual strategies for the use of eye-movement modeling examples in ATC training. Chapter 3 presents a study that investigates the regulation skills required to be a successful ATC student and how cognitions of different stakeholders differ as to these requirements. This chapter employs focus groups with three different groups of stakeholders (i.e., training designers, trainers/coaches, students) to determine those skills that must be trained when preparing students to learn throughout their ATC careers. The study sheds light on the learning characteristics required for successfully learning ATC. Moreover, the chapter provides insight in the mutual relation between two groups of regulation skills: self-regulated learning (SRL; Zimmerman, 1990) and self-directed learning (SDL; Knowles, 1975, Van Merriënboer & Sluijsmans, 2009) and takes into account the mediation of student engagement and self-efficacy on SRL and SDL. The differences between cognitions of successful training in ATC give insight how instructional designers, trainees and coaches differ. Chapter 4 presents a theoretical framework for combining the training of complex cognitive skills with the development of regulation skills. It is based on the premise that it is best to use shared control in the task selection process. This framework also deals with the paradox that a system that trains regulation skills also requires students to have already developed regulation skills (Corbalan, Van Merriënboer, & Kicken, 2010). Shared control in task selection aims at increasing the responsibility of learners for selecting their own learning tasks. This responsibility should activate the learners to think about their own learning challenges. By discussing both the system and the required attitude of coaches and students in such an environment, insight is gained with respect to the requirements for the elements (i.e., task database, portfolio) employed in it. A coaching protocol is also introduced to support the coaches in using the system’s elements to involve the students in their own learning process. Chapter 5 presents an empirical study testing the idea of training self-regulation skills in combination with domain-specific competences. The study is carried out in the everyday practice of ATC training. The chapter describes the design of learning tasks and the role of a development portfolio in such learning environments. The increase of learning in both domain-specific skills and self-regulation skills is measured. Finally, Chapter 6 discusses the overall conclusion that can be drawn from the thesis in light of training improvements in cognitively complex domains. The chapter than discusses the theoretical and practical implications of the studies and concludes with the limitations of the studies and with ideas for future research.Sponsorship: Knowledge & Development Centre, Mainport Schiphol

In this dissertation, the focus is on learning in workplace simulations and the quest toward self-regulation in vocational education. The main aim was to gain understanding in the kind of difficulties and success factors students and teachers experience in workplace simulations, identify and explore self-regulated actions and to seek ways to support students’ self-regulated learning skills in the instructional design and feedback. One theoretical article and 4 empirical studies were conducted and are described in detail.