Effects of tutor-related behaviours on the process of problem-based learning

Tutors in a Problem-Based Learning (PBL) curriculum are thought to play active roles in guiding students to develop frameworks for use in the construction of knowledge. This implies that both subject-matter expertise and the ability of tutors to facilitate the learning process must be important in helping students learn. This study examines the behavioural effects of tutors in terms of subject-matter expertise, social congruence and cognitive congruence on students’ learning process and on their final achievement. The extent of students’ learning at each PBL phase was estimated by tracking the number of relevant concepts recalled at the end of each learning phase, while student achievement was based on students’ ability to describe and elaborate upon the relationship between relevant concepts learned. By using Analysis of Covariance, social congruence of the tutor was found to have a significant influence on learning in each PBL phase while all of the tutor-related behaviours had a significant impact on student achievement. The results suggest that the ability of tutors to communicate informally with students and hence create a less threatening learning environment that promotes a free flow exchange of ideas, has a greater impact on learning at each of the PBL phases as compared to tutors’ subject-matter expertise and their ability to explain concepts in a way that is easily understood by students. The data presented indicates that these tutor-related behaviours are determinants of learning in a PBL curriculum, with social congruence having a greater influence on learning in the different PBL phases

Are tutor behaviors in problem-based learning stable? A generalizability study of social congruence, expertise and cognitive congruence

The purpose of this study was to investigate the stability of three distinct tutor behaviors (1) use of subject-matter expertise, (2) social congruence and (3) cognitive congruence, in a problem-based learning (PBL) environment. The data comprised the input from 16,047 different students to a survey of 762 tutors administered in three consecutive semesters. Over the three semesters each tutor taught two of the same course and one different course. A generalizability study was conducted to determine whether the tutor behaviors were generalizable across the three measurement occasions. The results indicate that three semesters are sufficient to make generalizations about all three tutor behaviors. In addition the results show that individual differences between tutors account for the greatest differences in levels of expertise, social congruence and cognitive congruence. The study concludes that tutor behaviors are fairly consistent in PBL and somewhat impervious to change. Implications of these findings for tutor training are discussed

Machine and human observable differences in groups’ collaborative problem-solving behaviours

This paper contributes to our understanding of how to design learning analytics to capture and analyse collaborative problem-solving (CPS) in practice-based learning activities. Most research in learning analytics focuses on student interaction in digital learning environments, yet still most learning and teaching in schools occurs in physical environments. Investigation of student interaction in physical environments can be used to generate observable differences among students, which can then be used in the design and implementation of Learning Analytics. Here, we present several original methods for identifying such differences in groups CPS behaviours. Our data set is based on human observation, hand position (fiducial marker) and heads direction (face recognition) data from eighteen students working in six groups of three. The results show that the high competent CPS groups spend an equal distribution of time on their problem-solving and collaboration stages. Whereas, the low competent CPS groups spend most of their time in identifying knowledge and skill deficiencies only. Moreover, as machine observable data shows, high competent CPS groups present symmetrical contributions to the physical tasks and present high synchrony and individual accountability values. The findings have significant implications on the design and implementation of future learning analytics systems

Self-reflection and academic performance: is there a relationship?

The purposes of the present study were two-fold: first, to evaluate whether reflection journal writing was effective in promoting self-reflection and learning, and whether students become better at self-reflection if they engage continuously in reflection journal writing. To that end, the reflection journals of 690 first-year applied science students at a local polytechnic were studied by means of an automated coding procedures using software. Data was collected twice, once at the beginning and again towards the end of an academic year. Outcomes of the textual content analyses revealed that students reflected on both the process and contents of their learning: critical review of past learning experiences, learning strategies and summaries of what was learned. Correlational analyses showed weak to moderate inter-relationship

Designing citizen science tools for learning: lessons learnt from the iterative development of nQuire

This paper reports on a 4-year research and development case study about the design of citizen science tools for inquiry learning. It details the process of iterative pedagogy-led design and evaluation of the nQuire toolkit, a set of web-based and mobile tools scaffolding the creation of online citizen science investigations. The design involved an expert review of inquiry learning and citizen science, combined with user experience studies involving more than 200 users. These have informed a concept that we have termed ‘citizen inquiry’, which engages members of the public alongside scientists in setting up, running, managing or contributing to citizen science projects with a main aim of learning about the scientific method through doing science by interaction with others. A design-based research (DBR) methodology was adopted for the iterative design and evaluation of citizen science tools. DBR was focused on the refinement of a central concept, ‘citizen inquiry’, by exploring how it can be instantiated in educational technologies and interventions. The empirical evaluation and iteration of technologies involved three design experiments with end users, user interviews, and insights from pedagogy and user experience experts. Evidence from the iterative development of nQuire led to the production of a set of interaction design principles that aim to guide the development of online, learning-centred, citizen science projects. Eight design guidelines are proposed: users as producers of knowledge, topics before tools, mobile affordances, scaffolds to the process of scientific inquiry, learning by doing as key message, being part of a community as key message, every visit brings a reward, and value users and their time

Student and tutor perceptions on attributes of effective problems in problem-based learning

This study aimed to identify the attributes that students and tutors associated with effective PBL problems, and assess the extent to which these attributes related to the actual effectiveness of problems. To this end, students and tutors in focus groups were asked to discuss about possible attributes of effective problems. The same participants were then asked to individually and independently judge eight sample problems they had worked with. Text analysis of the focus group discussion transcripts identified eleven problem attributes. Participants' judgments of the sample problems were then frequency-scored on the eleven problem attributes. Relating the participants' judgments with the entire student cohort's grades yielded high and significant correlations, suggesting that the eleven problem attributes reflect aspects of problem effectiveness

The relationships between problem characteristics, achievement-related behaviors, and academic achievement in problem-based learning

This study investigated the influence of five problem characteristics on students' achievement-related classroom behaviors and academic achievement. Data from 5,949 polytechnic students in PBL curricula across 170 courses were analyzed by means of path analysis. The five problem characteristics were: (1) problem clarity, (2) problem familiarity, (3) the extent to which the problem stimulated group discussion, (4) self-study, and (5) identification of learning goals. The results showed that problem clarity led to more group discussion, identification of learning goals, and self-study than problem familiarity. On the other hand, problem familiarity had a stronger and direct impact on academic achievement