Faciliter l’autorégulation de l’enseignement

Un·e enseignant·e universitaire qui souhaite réguler ses pratiques professionnelles pour répondre aux besoins des apprenant·e·s est parfois en déficit d’informations pour identifier les actions à entreprendre. Afin de permettre de dépasser son ressenti et ses propres impressions, deux Hautes Écoles pédagogiques de Suisse romande ont développé un outil numérique nommé OURA, qui a pour but de soutenir la régulation des activités d’enseignement/apprentissage au niveau universitaire. Cet article expose les fondements théoriques qui étayent son développement : d’abord les démarches de data-based decision-making et d’analytique de l’enseignement, puis les fondements théoriques des différents domaines et dimensions pris en compte dans l’outil.

Implementation of Data-Based Decision-Making: Linking Research From the Special Series to Practice

The papers in the special series describe the role of data-based decision-making (DBDM) in improving the outcomes of students with learning disabilities based on research across Germany, the Netherlands, and the United States. The articles address multiple aspects of a model of DBDM that includes the role of teacher knowledge, skills, beliefs, and sources of professional learning and the role of systems-level factors in improving student achievement. In this article, the conclusions of each paper are described in terms of that model. The papers illustrate that DBDM can improve achievement for students with learning disabilities through a DBDM process called data-based individualization (DBI)—especially if teachers have innovative supports (e.g., new technologies). For teachers, DBDM professional development (PD) can improve DBDM knowledge and implementation, but PD may not be adequate in all cases, with practical experience playing a central role. In addition, classroom-level DBDM may not translate to success for students with learning disabilities. Finally, the articles reveal a need to focus more on systems-level factors in successful DBDM systems like DBI—especially when implemented outside the experimental context. These findings provide a contemporary lens on DBDM as it related to students with learning disabilities and establish foci for future research.

Data-based decision-making in maintenance service delivery: the D3M framework

PurposeThis paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.Design/methodology/approachThe Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.FindingsThe interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities.Originality/valueThe paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

Effects of Data-Based Decision-Making on Low-Performing Readers in General Education Classrooms: Cumulative Evidence From Six Intervention Studies

In most general education classrooms in Germany, students with and without special educational needs are taught together. To support teachers in adapting instruction to these heterogeneous classrooms, we have developed learning progress assessment (LPA) and reading instructional materials, the Reading Sportsman (RS) in line with the theoretical framework of data-based decision-making, which has led to beneficial effects in several studies. However, data from these studies have not been analyzed to examine effects for low-performing readers. Data within and across six quasi-experimental studies conducted by our team in Grades 2 to 4 were reanalyzed to examine the effects of LPA on students whose reading fluency scores were at or below the 25th percentile ( n = 1,346 students from 264 classes). In each study, students had been assigned to a control group (with business-as-usual instruction), an LPA group only, or an LPA-RS group (i.e., with teachers provided with LPA and the RS). Separate multilevel regression results were integrated by means of meta-analytical methods to investigate the consistency of results. Overall, findings from the single studies indicated no positive effects of LPA with or without the RS compared with the control group. The integrated analyses showed small positive effect trends on reading fluency and intrinsic reading motivation.

A Systematic Review of CBM Professional Development Materials: Are Teachers Receiving Sufficient Instruction in Data-Based Decision-Making?

The purpose of this study was to examine the amount of attention devoted to data-based decision-making in Curriculum-Based Measurement (CBM) professional development materials. Sixty-nine CBM instructional sources were reviewed, including 45 presentations, 22 manuals, and two books. The content of the presentations and manuals/books was coded into one of four categories: (a) general CBM information, (b) conducting CBM, (c) data-based decision-making, and (d) other. Results revealed that only a small proportion of information in the CBM instructional materials was devoted to data-based decision-making (12% for presentations and 14% for manuals/books), and that this proportion was significantly smaller than (a) that devoted to other instructional topics, (b) that expected were information to be equally distributed across major instructional topics, and (c) that recommended by experienced CBM trainers. Results suggest a need for increased attention to data-based decision-making in CBM professional development.

Using Evidence-Based Practice and Data-Based Decision Making in Inclusive Education

There are longstanding calls for inclusive education for all regardless of student need or teacher capacity to meet those needs. Unfortunately, there are little empirical data to support full inclusion for all students and even less information on the role of data-based decision making in inclusive education specifically, even though there is extensive research on the effectiveness of data-based decision making. In this article, we reviewed what data-based decision making is and its role in education, the current state of evidence related to inclusive education, and how data-based decision making can be used to support decisions for students with reading disabilities and those with intellectual disabilities transitioning to adulthood. What is known about evidence-based practices in supporting reading and transition are reviewed in relationship to the realities of implementing these practices in inclusive education settings. Finally, implications for using data-based decisions in inclusive settings are discussed.

Educator Perspectives on Data-Based Decision Making in Germany and the United States

The purpose of this explorative study was to examine the use and understanding of key components of data-based decision making by educators in two countries—Germany and the United States. Educators responded to a survey that asked about data use and characteristics related to data-based decision making (DBDM). Results suggest educators in both countries are focused on using data to monitor progress, although less so in Germany. Educators in both countries noted similar understanding of important features (e.g., psychometric properties) of data. Educators in the United States reported they used data for decision making at the classroom level almost twice as often as their counterparts in Germany, while German educators focused on decision making at the student level. These findings will influence future research, including joint studies that could use the best practices of both countries, and professional learning opportunities for educators in Germany and the United States.