Learning Trajectories Research Articles

Designing Inclusive Computational Thinking Learning Trajectories for the Youngest Learners

Foundational thinking for later use of technology, particularly coding, is necessary for an inclusive and sustainable future. Inclusive practices beginning in early childhood recognize children’s innate development of computational thinking—sequencing, repetition and looping, debugging, decomposing and composing, representation, and causality. This qualitative research describes processes of developing and evaluating hypothesized developmental progressions. Inclusive engagement of children with and without disabilities is described in examples for each level of each developmental progression. Implications for teaching and learning with inclusive practices are described for children with and without disabilities.

The project-based learning model of training engineers: exploring opportunities for building an individual learning trajectory from the students’ and instructors’ perspectives

Introduction. The project-based approach into engineering training is an innovative education practice that exemplifies the UNESCO strategy for implementing such practices in education worldwide. The motivation of the study is justified by the fact that the implementation of project-based learning involves building a student learning trajectory, which meets demands for competitive specialists in the automotive industry. The research aimed to investigate opportunities for building students’ learning paths in correlation with the formal performance of the project-based learning model and to elicit issues for its improving. Materials and methods. The study used analysis of previous research and formal performance indicators of the project activity at the Mechanical Engineering Center, where pilot engineering training was launched at Togliatti State University (TSU, Russian Federation). To collect empirical data, an online survey was administered among 118 engineering students (its reliability reached Cronbach’s alpha 0.84), and unstructured and focused interviews among student advisors and project supervisors were conducted. Methods of descriptive statistics and IBM SPSS Statistics 23 package were employed to process the obtained quantitative data. Research results. Quantitative performance indicators of the model demonstrate overall positive dynamics in engineers’ training from 2017 to the present. The study discovered project satisfaction at the Mechanical Engineering Centre (74.1%) and the majority of students (71.9%) evaluate positively project opportunities. The correlation between the project role and the awareness of project opportunities was found (r = 0.23; p < 0.05): all student advisors considered project activity as an opportunity to develop their learning trajectory. However, 14.9% of participants did not consider such project prospects. The focused interview clarified reasons for this choice. Conclusion. The study shows that the correlation between the positive dynamics of formal indicators and assessments of the opportunities of building an individual learning trajectory reveals the need to improve the introduced model in terms of finding the optimal balance between the number of projects and their quality. The study prospects include the formation of students’ readiness and internal motivation for participating in engineering projects. The TSU experience in evaluating the opportunities of forming students’ learning paths through project participation can be helpful for other Russian universities where project-based learning is implemented.

Blended pedagogy for computer programming language

In the face of the challenges posed by the COVID-19 pandemic, the hybrid teaching model has garnered significant attention for its combination of the depth of traditional education with the convenience of distance learning. Focusing on the domain of computer programming language instruction, this study innovatively designs a hybrid teaching strategy aimed at fully exploiting the flexibility of its teaching design and the variety of pedagogical approaches. The strategy integrates face-to-face teaching with online autonomous learning, incorporating project-based teaching methodologies and immediate feedback mechanisms to facilitate active student engagement and deep learning. Through a year-long practice in a C++ programming course, encompassing 68 students, the study empirically validates the effectiveness of the hybrid teaching approach. It not only demonstrates remarkable educational outcomes, enhancing the quality of programming instruction and student satisfaction with their learning experience, but also employs Bayesian analysis to delve into the relationship between learning trajectories and students’ sense of self-efficacy. By focusing on key indicators during the learning process, such as the timeliness and quality of online learning, laboratory work, and project assignments, the study then utilizes Bayesian models to directly assess the impact of these learning behavior metrics on students’ perceived self-efficacy. The findings reveal that students with outstanding academic achievements exhibit higher levels of self-efficacy, confirming that academic performance can reasonably reflect teaching effectiveness and provide a quantifiable basis for assessing individual learning progress. Consequently, this research not only contributes a novel strategy to computer programming education practice but also offers a valuable reference for the application of hybrid teaching models in other disciplines. Furthermore, it promotes in-depth contemplation on post-pandemic innovations in teaching modes and issues of educational equity, laying a solid foundation for constructing a more adaptive and inclusive future education system.

Assessment of vocabulary comprehension in Bilingual Qom - Spanish Indigenous children in Northern Argentina: Evidence for education, language preservation, and psycholinguistic theory

In this study we adapted the Computerized Comprehension Task (CCT), to be used in rural native communities with bilingual children learning Qom Indigenous language and the Chaco dialect of Argentinean Spanish. The main objectives were (a) to test the utility of this task, which provides accuracy and response time measures of decontextualized vocabulary, for use with children from three to seven years in schools and rural settings; (b) to assess Qom children’s vocabulary learning trajectories in both languages. The adaptation of the CCT was based on extensive fieldwork establishing language usage patterns, word frequency, and age of acquisition. Eighty-three children from three to seven years of age living in Chaco Province were assessed in Qom and Spanish, employing the CCT adaptation. Findings provided evidence of attrition of children’s heritage language (which is on par with vocabulary in the majority language up until age five), beginning as children approach elementary school.

Preliminary Design of Learning the Lowest Common Multiple (LCM) and Greatest Common Factor (GCF) Using the RADEC Learning Model

Learning obstacles were found in students who studied LCM and GCF. This research aims to develop an initial design in the form of a hypothetical learning trajectory for LCM and GCF using the RADEC (Read, Answer, Discuss, Explanation, and Create) learning model which is based on obstacles learning findings. This research is part of the design research method. The design research method consists of preliminary design, teaching experiment, and retrospective analysis. The focus of this research is the preliminary design stage. Based on the results, it is known that students have difficulties in solving questions on LCM and GCF material, namely that students cannot use the concepts of LCM and GCF to solve problems, students tend to think that the concepts of LCM and GCF are only factor trees or procedural factorization, and students do not understand the concepts of LCM and GCF. To overcome these learning obstacles, a hypothetical learning trajectory for the LCM and GCF was prepared using the RADEC learning model which was divided into three meetings. The first meeting was about multiples, common multiple, and LCM. The second meeting was about factors, common factors, and GCF. The third meeting was regarding determining the LCM and GCF using prime factorization. Each learning flow from each meeting is described in the form of HLT which consists of learning objectives, learning activities, and student thinking estimates. The theoretical implications in this research are the new findings of HLT LCM and GCF with the RADEC learning model and practical implications in this research are that HLT can be used as a consideration for teachers in designing LCM and GCF learning by paying attention to students' learning trajectories.

HYPOTHETICAL LEARNING TRAJECTORY DESIGN IN REFLECTION LEARNING USING THE CONTEXT OF THE CIREBON RED MOSQUE

This research aims to design a reflective learning trajectory using the context of the Cirebon Red Mosque as the starting point or learning context. The method used in this research is design research with stages of preliminary design, design experiment and retrospective analysis. The subjects in this research were several samples of class VIII junior high school students. The results of this research are a hypothetical learning trajectory design in reflective learning using the context of the Cirebon Red Mosque with a learning trajectory, namely students observing pictures from the front gate of the Red Mosque, having discussions and finding the meaning and properties of reflection, students drawing objects with agreed conditions, students record the starting point and ending point of the reflection results and find the relationship between the two and finally, students find the reflection formula. The research results show that a series of activities in the context of the Cirebon Red Mosque have a potential impact on understanding the concept of reflection. Students work on mathematics collaboratively and the learning process becomes meaningful and easy.

Classification and Analysis of the Application of Knowledge Graphs in Education

A classification of the use of knowledge graphs in the educational field is presented and analyzes the methods used is carried out. The lack of systematization of the use of knowledge graphs in education, adapted to the individual needs and interests of various stakeholders, has necessitated the analysis and classification of the use of knowledge graphs in education, taking into account the key participants in the educational process. The purpose of the article is to classify the use of knowledge graphs by key participants in the educational field and analyze the methods used to construct and manipulate knowledge graphs. The research methodology is based on review, analysis, classification of scientific articles and projects. As a result of the analysis, several conclusions were obtained. The most common application of knowledge graphs is their use as an educational environment for students, serving as a tool for learning specific subject areas. Teachers perceive knowledge graphs as a means of organizing and structuring educational materials, and education managers consider them valuable for constructing individual learning trajectories and as auxiliary tools for decision making. Various authors have proposed a variety of approaches to working with knowledge graphs, using a variety of techniques such as machine learning, natural language processing algorithms, ontology creation, expert assistance, and the use of a wide range of models. The general trend is that methods for working with knowledge graphs often combine different approaches and technologies to achieve maximum efficiency in solving specific problems. The possibility of further application of the results is to identify the least covered group of stakeholders and develop for them a model of a recommendation system based on knowledge graphs, using modern and relevant methods for processing them.

Мобильное приложение для развития лидерских качеств с интеллектуальной индивидуализацией траектории обучения

В статье рассматривается разработка мобильного игрового приложения для формирования и развития лидерских качеств у школьников старших классов, студентов колледжей и техникумов. Обучающее игровое приложение соответствует концепции «инновационной образовательной технологии», то есть включает в себя комплекс из трех взаимосвязанных составляющих: современное содержание, современные методы обучения, современная цифровая инфраструктура обучения. Разработанное мобильное приложение позволяет системно развивать такие лидерские качества, как уверенность в себе, ответственность, умение планировать время, креативность, умение действовать в ситуации неопределенности, целеустремленность. В основе логики приложения заложен принцип формирования индивидуальной образовательной траектории. Для построения индивидуальных траекторий обучения для каждого пользователя используется нейросетевая кластеризация анкетных данных. То есть при генерации индивидуальных траекторий развития лидерских качеств используются не только методы анкетирования, но и результат применения к совокупности анкет методов кластеризации. Для кластеризации используются самоорганизующиеся карты Кохонена. Получаемое разбиение на кластеры проанализировано экспертами, выявлено несколько четко обозначенных кластеров, для каждого из которых составлена модель индивидуального изменения траектории развития лидерских качеств. В результате экспертного анализа результатов кластеризации было выделено семь кластеров. Совместно с экспертами составлено описание каждого кластера. The article discusses the development of a mobile gaming application for the formation and development of leadership qualities in high school students, college and technical school students. The educational gaming application corresponds to the concept of "innovative educational technology", that is, it includes a set of three interrelated components: modern content, modern teaching methods, modern digital learning infrastructure. The developed mobile application allows you to systematically develop such leadership qualities as self-confidence, responsibility, time management skills, creativity, the ability to act in a situation of uncertainty, and determination. The application logic is based on the principle of forming an individual educational trajectory. To build individual learning trajectories for each user, neural network clustering of questionnaire data is used. That is, when generating individual trajectories for the development of leadership qualities, not only questionnaire methods are used, but also the result of applying clustering methods to a set of questionnaires. Self-organizing Kohonen maps are used for clustering. The resulting division into clusters was analyzed by experts, several clearly defined clusters were identified, for each of which a model of individual change in the trajectory of development of leadership qualities was compiled. As a result of expert analysis of the clustering results, seven clusters were identified. A description of each cluster was compiled jointly with experts.

Facilitating self-management support using the behaviour change wheel (BCW) to address healthcare professionals’ behaviour

BackgroundSupporting self-management in healthcare practice is essential to improve chronic patients’ daily life experiences. Primary care professionals play an indispensable role in this. Nevertheless, supporting self-management in practice comes with many challenges. The aim of this study is to identify determinants of professionals’ supportive behaviour and develop an intervention that facilitates self-management support in primary care practice, using these determinants as building blocks. MethodsTo develop the intervention, the Behaviour Change Wheel (BCW) was used which involves eight steps in three stages: (1) Understanding the behaviour using the COM-B model, (2) Identifying intervention options, and (3) Identifying content and implementation options. The theoretical underpinnings for stage 1 included data from interviews, focus groups and brainstorm sessions, incorporated beforehand in a self-management support model. Subsequently, literature analysis, empirical research and expertise from the research group guided stages 2 and 3. ResultsWe found that changes in “psychological capability”, “physical opportunity”, “reflective motivation” and “automatic motivation” are required to optimize professionals’ behaviour towards self-management support. The two key intervention functions identified were “enablement” and “education”. Therefore, a blended learning trajectory that incorporated these interventional building blocks was developed, integrating specific behaviour change techniques (BCTs) including: (1) Information about social and environmental consequences, (2) Information about health consequences, and (3) Social support (practical). The learning design was finalized by applying the Absorb-Do-Connect learning framework developed by Horton. ConclusionsApplication of the BCW framework shaped a self-management support intervention to educate and enable healthcare professionals. Future research will pilot and refine the intervention.

Development of Arabic Language Learning in Indonesia at 19th – 21st Century

Arabic language learning has a long history in Indonesia, starting from the 19th century. This article aimed to provide a comprehensive historical overview of the development of Arabic language learning in Indonesia from the 19th century to the 21st century. A qualitative approach and the historical review method with quasi descriptive research model were applied. This article examined the evolution of teaching methods, curriculum and media used in Arabic language learning. In this research, the primary sources were the official reports, curriculum, textbooks, journals, and historical records, as well as secondary sources such as academic literature and research publications. This article traced the shifts and transformations in Arabic language teaching practices in Indonesia. Through content analysis and historical interpretation, key milestones, trends and factors were identified which shaped the trajectory of Arabic language learning over the past three centuries. The findings revealed diverse influences, ranging from the traditional Islamic education system to modern learning models that keep up with the times. This article highlighted the unique challenges and adaptations that have characterized the development of Arabic language learning in Indonesia. By offering a historical perspective on the evolution of Arabic language learning methods and approaches, this article contributed to a deeper understanding of the current state of Arabic language education in Indonesia. The insights gained from this research could inform the future strategies and policies aimed at improving the quality and effectiveness of Arabic language learning and preserving the nation's cultural and linguistic heritage.

Finnish open university education and students’ transitions into and within higher education

There is a growing number of higher education (HE) students who do not follow the conventional sequential progression from the beginning to the end of their studies. Instead, they may use alternative admission routes, take gap years, delay their studies and transfer from one discipline or institution to another. In particular, students from under-represented social groups tend to follow less linear trajectories. In this article, we are interested in the institutional policies and practices that enable multiple ways for students to navigate into and within HE. As a theoretical lens, we apply Gale and Parker’s typology of student transition and the conceptualisation of transition as ‘becoming,’ which entails rejecting the notion of linearity and normativity. Our empirical case is Finnish open university education (OUE). Using student interviews (N=16) and reflexive thematic analysis, we identified three institutional characteristics: openness of access, flexible mode of studies, and alternative access route to degree studies. These characterisics enabled highly individualised learning trajectories and opportunity to enter, withdraw and return to OUE throughout life. However, the OUE gateway was selective, which limited its potential to reduce social inequality in student transitions. The study advances the policy discussion and development of inclusive universities.

Different Languages, Different Mathematics Learning

Culture shapes pupils’ mathematical learning, their performances and life trajectories of participation (César, 2013a, 2013b). It also contributes to the senses they attribute to mathematical learning (Bakhtin, 1929/1981). Using collaborative work and inter-empowerment mechanisms facilitates knowledge appropriation (César, 2009). This is particularly important for pupils participating in minority cultures, socially undervalued and whose L1 is not the instruction language. Bi-univocal culture mediation (César, 2017b) is important regarding empowerment. We used an instrument to evaluate pupils’ abilities and competencies (IACC), conceived by the Name of the Project team (Machado, 2014), and other mathematical tasks. The goal we address is to trace the differences between their approaches to problems, mathematical reasoning and solving strategies used by pupils whose L1 is ideographic (Creole, Cape Verde) or phonetic (Portuguese). We developed an intrinsic case study (Stake, 1995). The main participants are the pupils from almost 600 classes (all over Portugal and Cape Verde) who participated in the Name of the Project. The analysis of some examples illustrates that L1 shapes pupils’ approaches to problems, mathematical reasoning and solving strategies. This evidence plays an important role in their access to school achievement and in teachers’ understanding about how they can promote pupils’ mathematical learning.

Learning Plan Use in Undergraduate Medical Education: A Scoping Review.

How to best support self-regulated learning (SRL) skills development and track trainees' progress along their competency-based medical education learning trajectory is unclear. Learning plans (LPs) may be the answer; however, information on their use in undergraduate medical education (UME) is limited. This study summarizes the literature regarding LP use in UME, explores the student's role in LP development and implementation, and identifies additional research areas. MEDLINE, Embase, PsycInfo, Education Source, and Web of Science databases were searched for articles published from database inception to March 6, 2024, and relevant reference lists were manually searched. The review included studies of undergraduate medical students, studies of LP use, and studies of the UME stage in any geographic setting. Data were analyzed using quantitative and qualitative content analyses. The database search found 7,871 titles and abstracts with an additional 25 found from the manual search for a total of 7,896 articles, of which 39 met inclusion criteria. Many LPs lacked a guiding framework. LPs were associated with self-reported improved SRL skill development, learning structure, and learning outcomes. Barriers to their use for students and faculty were time to create and implement LPs, lack of training on LP development and implementation, and lack of engagement. Facilitators included SRL skill development, LP cocreation, and guidance by a trained mentor. Identified research gaps include objective outcome measures, longitudinal impact beyond UME, standardized framework for LP development and quality assessment, and training on SRL skills and LPs. This review demonstrates variability of LP use in UME. LPs appear to have potential to support medical student education and facilitate translation of SRL skills into residency training. Successful use requires training and an experienced mentor. However, more research is required to determine whether benefits of LPs outweigh the resources required for their use.

How story problems strengthen arithmetic problem-solving strategy sophistication: Evidence from a learning trajectory teaching experiment in kindergarten

BackgroundThe sophistication of young children's arithmetic problem-solving strategies can be influenced through experience and instructional intervention. One potential pathway is through encountering story problems where the location of the unknown quantity varies. AimsThe goal of the present study is to characterize how arithmetic problem-solving strategy sophistication can evolve through opportunities to solve story problems. SampleWe used microgenetic principles to guide the coding of arithmetic problem-solving behavior (8843 attempts) across three timescales (time within-session, attempt to solve, and between sessions) for nine story problem structures (N = 40, 19 girls). Data come from a teaching experiment conducted in a Mountain West US state in Spring 2018. MethodsWe employed a Bayesian hierarchical ordinal regression with a nine-level response variable. The model contained fixed effects for session, attempt, story problem structure; a smooth time within session effect; and random effects for student, instructor, and equation. ResultsOur analysis indicates which transitions from less to more sophisticated strategies are better supported by additional attempts to solve the same problem vs. additional instructional sessions. Strategy sophistication also varied by the location of the unknown quantity (result unknown, find difference, start unknown), but not operation (join, separate, part-whole). ConclusionsIf confirmed by other studies, including experiments, what teachers offer children in terms of learning opportunities (more attempts within the same problem or more problems across work sessions) should vary based on the transition they are making.

Development of a 21st Century Based Mathematics Learning Model: A Validity Study on the Investigation-Construction Stages

<p style="text-align:justify">The purpose of this study was to develop a valid and theoretically sound 21st century skills-based mathematics learning model. Plomp's research and development theory and Nieveen's criteria were used to ensure the quality and reliability of the model. The model development process includes Initial Investigation, Design, and Realization/Construction. Data were collected from six schools through various instruments such as observation sheets, documents, 21st century skills tests, and interview guides. Model validation involved the participation of five experts. A blended data analysis approach was used to ensure a comprehensive understanding of the findings. The result of this study is a 21st century skills-based mathematics learning model named Model 21-BML. The model consists of five interconnected core components: Learning Syntax, Social System, Reaction Principles, Support System, and Instructional and Accompanying Impacts. The uniqueness of this model lies in the seven integrated learning trajectories: Object translation, decomposition, cognitive construction, cognitive development, communication, reflection, and extension. After going through a rigorous validation process, the five experts confirmed the high validity of the 21-BML Model. This model not only enhances innovative mathematics learning theory, but also provides practical alternatives for mathematics teachers to encourage the development of 21st century skills in students. The model is expected to make a significant contribution in bridging the gap between traditional mathematics education and the competency demands of the modern era, as well.</p>

Individual differences in working memory impact the trajectory of non-native speech category learning.

What is the role of working memory over the course of non-native speech category learning? Prior work has predominantly focused on how working memory might influence learning assessed at a single timepoint. Here, we substantially extend this prior work by examining the role of working memory on speech learning performance over time (i.e., over several months) and leverage a multifaceted approach that provides key insights into how working memory influences learning accuracy, maintenance of knowledge over time, generalization ability, and decision processes. We found that the role of working memory in non-native speech learning depends on the timepoint of learning and whether individuals learned the categories at all. Among learners, across all stages of learning, working memory was associated with higher accuracy as well as faster and slightly more cautious decision making. Further, while learners and non-learners did not have substantially different working memory performance, learners had faster evidence accumulation and more cautious decision thresholds throughout all sessions. Working memory may enhance learning by facilitating rapid category acquisition in initial stages and enabling faster and slightly more careful decision-making strategies that may reduce the overall effort needed to learn. Our results have important implications for developing interventions to improve learning in naturalistic language contexts.

Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care

There has recently been an increase in ongoing patient-report routine outcome monitoring for individuals within clinical care, which has corresponded to increased longitudinal information about an individual. However, many models that are aimed at clinical practice have difficulty fully incorporating this information. This is in part due to the difficulty in dealing with the irregularly time-spaced observations that are common in clinical data. Consequently, we built individual-level continuous-time trajectory models of suicidal ideation for a clinical population (N = 585) with data collected via a digital platform. We demonstrate how such models predict an individual’s level and variability of future suicide ideation, with implications for the frequency that individuals may need to be observed. These individual-level predictions provide a more personalised understanding than other predictive methods and have implications for enhanced measurement-based care.

Enhancing conversational recommendation systems through the integration of KNN with ConLinUCB contextual bandits

In recommender system research, contextual multi-armed bandits have shown promise in delivering tailored recommendations by utilizing contextual data. However, their effectiveness is often curtailed by the cold start problem, arising from the lack of initial user data. This necessitates extensive exploration to ascertain user preferences, consequently impeding the speed of learning. The advent of conversational recommendation systems offers a solution. Through these systems, the conversational contextual bandit algorithm swiftly learns user preferences for specific key-terms via interactive dialogues, thereby enhancing the learning pace. Despite these advancements, there are limitations in current methodologies. A primary issue is the suboptimal integration of data from key-term-centric dialogues and arm-level recommendations, which could otherwise expedite the learning process. Another crucial aspect is the strategic suggestion of exploratory key phrases. These phrases are essential in quickly uncovering users potential interests in various domains, thus accelerating the convergence of accurate user preference models. Addressing these challenges, the ConLinUCB framework emerges as a groundbreaking solution. It ingeniously combines feedback from both arm-level and key-term-level interactions, significantly optimizing the learning trajectory. Building upon this, the framework integrates a K-nearest neighbour (KNN) approach to refine key-term selection and arm recommendations. This integration hinges on the similarity of user preferences, further hastening the convergence of the parameter vectors.

Preliminary findings from the longitudinal study of big picture learning Australia university pathway students

Year 12 students in Big Picture Learning schools across Australia now use portfolios and interviews to apply for and gain entry to their first choice of university degree. They receive admission on the strength of portfolio evidence mapped to a new non-ATAR qualification, known as the International Big Picture Learning Credential (IBPLC). Since 2020, 270 graduates have received offers to university using the Credential, growing from 3 in 2017. Like other Big Picture graduates who went before them, they are continuing a trajectory of passion-based learning that began in Year 9 or 10 at one of 45 Australian Big Picture Learning schools. All IBPLC graduates begin tertiary study equipped with experiences in the real world, support systems with a range of community mentors and teachers, specialist knowledge in their chosen field, and a set of independent learning skills intended to give them the opportunity to thrive in the university setting. In this article we share the preliminary findings of a study of graduates of Big Picture Learning Australia secondary schools who have matriculated using the IBPLC. Findings from our surveys and interviews show promise that the learning design of Big Picture, which starts with an internship in a passion area, is the key factor in enabling the success of graduates both from high school and into their university studies.

Not easy to get off track: Motivational trajectories of learners completing a non-formal online course

Non-formal learning is becoming increasingly important in everyday life. Both the availability of open online learning opportunities and the number of participants in online courses continue to grow. Initially learners report high levels of motivation, but completion rates tend to be low. In the present study, we examined motivational trajectories of learners completing a non-formal online course. To this end, 450 learners of 49 open online courses offered by Bavarian universities completed up to three online questionnaires throughout the course. First, we used latent profile analysis to explore motivational trajectories within five subtypes of situational motivation, which resulted in four different motivational profiles. However, all profiles were characterized by remarkable stability over time, and differences only in the actual levels of the five motivational subtypes. Second, we used bivariate latent change score models to focus on differences of change in intrinsic motivation when analyzing simultaneously with situational interest. In addition, we considered self-regulation and mastery goal orientation as predictors of change in motivation. For intrinsic motivation there was only a small mean change and compensating effect from T1 to T2. We discuss the findings in the light of the fact that there are high dropout rates in non-formal online courses and offer practical advice on how to better address non-completers in future research.