Cindy Louise Poortman

Data teams for school improvement

The use of data for educational decision making has never been more prevalent. However, teachers and school leaders need support in data use. Support can be provided by means of professional development in the form of “data teams”. This study followed the functioning of 4 data teams over a period of 2 years, applying a qualitative case study design. The findings show that data use is not a linear process, and that teams go through different feedback loops to reach higher levels of depth of inquiry. The data team procedure is a promising way of enhancing data-based decision making in schools.

Apprenticeship: From Learning Theory to Practice.

To meet the requirements of an increasingly innovative and competitive environment, workers need to continuously develop and maintain competence. Consequently, initial vocational education and training should prepare (future) workers by providing a basis for lifelong learning in developing both routine and flexible competence. The question is whether workplace learning in initial VET contributes to this aim. To describe WPL processes and outcomes in the Dutch senior VET context, we apply a further elaboration of a comprehensive workplace learning theory, comprising a cognitive, a social and an emotional dimension. Qualitative case studies show that various factors in the different dimensions of learning influence the learning processes and outcomes in a diverse way. Especially more profound acquisition and development of abstract principles relating to flexible competence does not automatically take place during WPL. To fulfill the expectations regarding the role of initial VET to contribute to learning to learn and lifelong learning, improvements are required.

Opening the black box: knowledge creation in data teams

Purpose – In this study, Nonaka and Takeuchi’s socialization, externalization, combination and internalization (SECI) model of knowledge creation is used to gain insight into the process of knowledge creation in data teams. These teams are composed of school leaders and teachers, who work together to improve the quality of education. They collaboratively create knowledge related to data use and to an educational problem they are studying. The paper aims to discuss these issues. Design/methodology/approach – A qualitative micro-process case study was conducted for two data teams. The modes, transitions and content of the knowledge creation process were analyzed for all data team meetings over a two-year period. In addition, all team members were interviewed twice to triangulate the findings. Findings – Results show that the knowledge creation process was cyclical across meetings, but more iterative within meetings. Furthermore, engagement in the socialization and internalization mode provided added value in this process. Finally, the SECI model clearly differentiated between team members’ processes. Team members who engaged more often in the socialization and internalization modes and displayed more personal engagement in those modes gained greater and deeper knowledge. Research limitations/implications – The SECI model is valuable for understanding how teams gain new knowledge and why they differ in those gains. Practical implications – Stimulation of active personal engagement in the socialization and internalization mode is needed. Originality/value – This is one of the first attempts to concretely observe the process of knowledge creation. It provides essential insights into what educators do in professional development contexts, and how support can best be provided.

Primary teachers conducting inquiry projects: effects on attitudes towards teaching science and conducting inquiry

ABSTRACT This study used an experimental, pretest-posttest control group design to investigate whether participation in a large-scale inquiry project would improve primary teachers’ attitudes towards teaching science and towards conducting inquiry. The inquiry project positively affected several elements of teachers’ attitudes. Teachers felt less anxious about teaching science and felt less dependent on contextual factors compared to the control group. With regard to attitude towards conducting inquiry, teachers felt less anxious and more able to conduct an inquiry project. There were no effects on other attitude components, such as self-efficacy beliefs or relevance beliefs, or on self-reported science teaching behaviour. These results indicate that practitioner research may have a partially positive effect on teachers’ attitudes, but that it may not be sufficient to fully change primary teachers’ attitudes and their actual science teaching behaviour. In comparison, a previous study showed that attitude-focused professional development in science education has a more profound impact on primary teachers’ attitudes and science teaching behaviour. In our view, future interventions aiming to stimulate science teaching should combine both approaches, an explicit focus on attitude change together with familiarisation with inquiry, in order to improve primary teachers’ attitudes and classroom practices.

Work-Study Programs for the Formation of Professional Skills

Policy-makers consider workplace learning as an effective strategy for the development of vocational, career and professional identity (Tynjala, Valimaa & Sarja, 2003).

Case Study: English Language Results

This chapter uses a second case study to extensively describe what working with the data team™ procedure is like in practice. This chapter describes the process for a team that worked on a subject-specific problem pertaining to English language results in the 10th grade. The team defined the following problem definition: “We are unhappy about the English achievement scores in the 10th grade, because the grade has been 5.5 on average over the past four years. We want the average grade in the 10th grade to be at least 5.9 next year and at least 6.1 the year after that.” The team investigates several hypotheses, concerning middle school location, 5th grade English achievement scores, scores from previous years, and reading skills. In this chapter we describe how the data team investigated these hypotheses, what their conclusions were, and how they were able to improve English language results based on the collected data.

Case: High School Graduation Rates

This chapter extensively covers what working with the data teamTM procedure is like in practice. It describes a team working on a school-wide problem regarding low graduation rates at their high school. It is loosely based on our experiences during the “Datateams” project, for which we supervised 37 teams as they worked with this method. In this chapter, a data team works on the following problem definition: “We are unhappy about the fact that an average of 32% of the students failed to graduate over the past three years. Next year, no more than 25% of the students may fail to graduate. The year after that, we want to reduce this percentage to no more than 20%.” The team investigates several hypotheses, concerning local graduation requirements and state requirements, student motivation, middle school scores, students cutting classes, feedback, and supervision. In this chapter, we describe how the data team investigated these hypotheses, what their conclusions were, and how they were able to improve graduation rates based on the collected data.

Introducing the Data Team™ Procedure in the School

This chapter describes what needs to be done when a school would like to start working with the data teamTM procedure. First of all, it is advisable to bring in external supervision from the start. Research into the data teamTM procedure shows that long-term external supervision is crucial to a team’s effectiveness. Secondly, there are some preliminary conditions that must be taken care of before adopting this method concerning characteristics of the data (e.g., what are the available data in the school), characteristics of the school organization (e.g., scheduled time for data team meetings), and individual and team characteristics (e.g., who joins the team). Thirdly, there are some factors that play a part during the process of data use. Several of these factors are important both as preliminary conditions and during the process itself. During the process, characteristics of the data (e.g., access to high quality data), characteristics of the school organization (e.g., data-informed leadership), and individual and team characteristics (e.g., data literacy) can enable or hinder the work of the data team.

The Road to Sustainability

Schools often start using the data team™ procedure with the ambition of making data use part of the school’s regular operations. Working with the data team™ procedure therefore has to transition from a one-time project into a sustainable change: a new “routine” implemented at all layers of the school to use data in discussions and when making decisions. In this chapter, we will describe three important factors for sustainability: (1) Keeping a record of the innovation through development of new procedures and materials, (2) professional development of personnel, and (3) organizational development regarding both structural and cultural aspects of the innovation. We will also describe three types of sustainability: (1) a sustainable solution to the problem the data team has investigated, (2) the continued use and integration of the data team™ procedure itself, and (3) data use within the school. In this chapter, we will describe how to work on these three types of sustainability.

Step 7: Implementing Improvement Measures

Once the team has identified a cause of the problem at hand, they can move on to step 7: taking improvement measures. However, just because the cause of a problem has been identified, this does not mean that it is also immediately clear what measure is best suited to address this cause. In step 7, teams therefore start by gathering ideas about what measures might resolve the problem at hand. In order to draw up a clear overview of measures, a team can make use of a variety of sources, such as the knowledge and experience of team members and colleagues in the school, networks such as the teacher’s union, practitioner journals, scientific literature, the internet and the experiences of other schools. Selecting the “right” measure from a list of possible measures often requires additional effort. The first step of this process is to verify whether the measure actually ties into the conclusions that have been formulated. Next, the team decides what criteria to use to compare the various measures and make the right choice. This can include such criteria as feasibility, proven effects, the expected speed of the effects and the costs of implementing the measure. Moving from measures to implementation requires a plan of action. A plan of action outlines the actions that need to be taken to implement each selected measure, who is to take these actions, what means are needed to do so and what the deadline is.