Tag Archives: ev-report

Evidence is primarily reporting on activity, with little or no evaluation data or rigorous qualitative research included.

Type: Evidence | Proposition: B: Teaching | Polarity: | Sector: | Country:

Causes of stagnation or even growth in the development of pupils are not in-depth researched, resulting in the effect that no appropriate plans can be developed or implemented.


In general primary schools have one or more digital systems with which they can register and monitor learning performance of students. The Ministry of Education, Culture and Science credited an important function to these student management systems. Conducting tests and analyzing the learning performance should be an important tool to improve education and improve learning outcomes (Ministry of Education, Culture and Science, 2007). Research by the Inspectorate of Education shows that schools who analyze their learning performance, and then adjust their teaching based on the results of these analyzes, indeed achieve higher output (Inspectorate of Education, 2010). Furthermore, in international literature the positive influence of using and analyzing student performance on the learning outcomes of students is supported (Feldman & Tung, 2001; Johnson, 2002).

To increase output, it is important that schools and school boards use the student management systems and correctly interpret the outcomes of analyzes, only then the results of analyzes can be used to improve education and output.

Various researchers, however, show that schools do not optimally use the possibilities of these digital student management systems (Meijer, Ledoux & Elshof, 2011; Visscher, Peters & Staman, 2010). Therefore, the purpose of this report is to provide information about the possibilities of digital student management systems, and on how the use of a digital student management system can lead to higher learning outcomes. Teachers, school boards and educational administrators can use the contents of this publication to assess and improve their own student management system (for this purpose included in the annexes is an instrument by means of which schools can determine their level of student management systems).

This report (in Dutch) also discusses and explains the following points:

  • why and how a student management system within a approach can result in better learning outcomes,
  • The specific support that digital student management systems can provide within result-oriented working (Hd. 2)
  • the current use student management systems at schools or school boards, and the conditions for student management systems (Hd. 3)
  • the various stages of use of student management systems (Hd. 4)
  • and finally, three inspiring examples of student management systems are described (Hd.5).

In compiling this report use has been made of the knowledge and experience from the Focus project of the University of Twente. In this project, 150 primary schools are trained in result-oriented working; the use of student management systems plays an important role.


This report describes what results-oriented working entails and how student monitoring systems can be supportive. Schools and school boards work result-oriented when they work systematically and purposefully with the aim of maximizing student achievement (Inspectorate of Education, 2010).

Teachers, schools and school boards need feedback on their actions and performance as a basis to monitor and improve their education and performance. The LVS (student management system) provides schools and school boards with important feedback. With LVS, and the associated Cito LVS tests they can receive feedback on the performance and development of individual students, groups of students and schools. To examine in-depth the causes of a stagnation, or even growth in the development of students, it is necessary to obtain other information with other instruments. This can, among others, be done by means of the analysis of the method-dependent tests, diagnostic interviews with students, but also with the aid of class observations.

However, research shows that schools are struggling with this last point. Causes of stagnation or even growth in the development of pupils are not in-depth researched, resulting in the effect that no appropriate plans can be developed or implemented.

If this is the case, then the LVS is only used as a measuring and viewing instrument, and not as a tool to improve educational practices. Often, a first awareness is needed to see that assessment data (also) say something about the quality of education, and that these data represent an important starting point for customizing and improving education.

In the report six stages of LVS have been formulated. These stages emerge from continued experiences within the Focus project, the steps are not supported empirically. The three practical examples indicate, however, that the structure of the pyramid can be retrieved within schools, and then in particular the distinction between the measurement and check phase and the phase where use leads to changes in teaching practice. In addition, these practical examples show that there is a tension between stage five and stage six. In stage five the school administrators use the LVS, amongst others, as an instrument with which they keep an eye on the performance of teachers, if this is not done properly it can lead to a blame culture.

When this is the case, the sixth stage of self-reflection, in which teachers from their own initiative systematically use performance feedback for their professional development, will not be reached. Furthermore, the use of LVS within a result-oriented approach can then result in undesirable side effects. In this way the focus on the learning outcomes can result in an increased pressure on students, teachers, schools and school boards which results in teaching to the test. Even fraud with assessment data is not inconceivable. Teachers and administrators must therefore be alert on the occurrence of such negative effects. Thus, it is important that a school culture is created in which teachers themselves can openly and safely discuss the results of their work, not as a basis for controlling the use of each other's actions, but to improve teaching quality based on quality feedback.

If we know better what (different) students need for their development and can better connect to these needs, the outcome will be that students also will learn more, which is ultimately what matters in result-oriented working.

Citation: Faber, M., Geel, M. van, Visscher, A. (2013) Digitale Leerlingvolgsystemen als basis voor Opbrengstgericht werken in het Primair Onderwijs, Universiteit Twente | Url: http://www.kennisnet.nl/uploads/tx_kncontentelements/Kennisnet_onderzoeksanalyse_LVS-gebruik_voor_OGW.pdf

Type: Evidence | Proposition: A: Learning | Polarity: | Sector: | Country:

Abstract: In the foreseeable future it will be technically possible for instructors, advisors and other delegated representatives of a college or university to access student participation and performance data in near-real time. One potential benefit of this increased data flow could include an improved ability to identify students at risk of academic failure or withdrawal. The availability of these data could also lead to creation of new adaptive learning measures that can automatically provide students personalized guidance.

Overview from the Hub: a presentation about what LectureTools records with view of this being used to provide real time data to teachers. A ‘study guide’ is generated from student notes submitted (in the LectureTools software) and ‘Lecture Clouds’ provided to students. Anecdotal feedback is positive and student wanted the cloud to provide links to  resources to help them better understand concepts (e.g. to their etextbook). No systematic qualitative evaluation is in evidence but this example represents a description of a real case of how analytics could help and add value to the system.

Citation: Samson, P. (2014) Analyzing Student Notes and Questions to Create Personalized Study Guides. The 4th International Conference on Learning Analytics and Knowledge. March 24-28, 2014. Indianapolis, USA. http://lak14indy.wordpress.com/lak-2014-conference-program-schedule/