Promoting the use of INVALSI data for scientific research and teaching.
The Seminar “INVALSI data: a tool for teaching and scientific research” will be held in Rome from 25th to 28th February 2021. This event, which has reached its 5th edition, has the purpose to promote the use of INVALSI data for scientific research and teaching. The data collected every year by INVALSI are a useful tool for investigating the characteristics of the Italian school system and for defining appropriate support or enhancement interventions. All interested parties are invited to submit research works based on INVALSI data.
We inform our kind users that, due to the recent events related to COVID-19, INVALSI has deemed it necessary to organize the 5th edition of the Seminar "INVALSI data: a tool for research and teaching" esclusively on-line.
Inequality situations at school: detection methods and best practices for the solution
Session co-organized with Espanet Italia
Scientific coordinator: Emmanuele Pavolini, Espanet Italia, Patrizia Falzetti, INVALSI
Equality is a fundamental principle of the school system. However, in recent years, extant research at both national and international level shows how inequalities among students have increased. Economic, social, gender and geographic differences have produced a school model that is struggling to guarantee equality. By investigating the indicators developed with INVALSI data, the contributions presented in this session will shed some more light on existing inequalities and help identifying best practices to be adopted so that the differences at school can be rebalanced.
Keywords: inequalities in learning, school, educational policies.
Learning analytics for improving the performance of students and institutions: methods, evidence and perspectives
Session co-organized with Politecnico di Milano
Scientific coordinator: Tommaso Agasisti, Politecnico di Milano, Patrizia Falzetti, INVALSI
In the context of recent studies on educational policies, ‘Learning Analytics (LA)’ means the innovative use of statistical, econometric and machine learning techniques to identify recurrences and relationships between the variables that influence the results of students and institutions. In particular, the concept of LA is referred to situations with large, deep and complex databases, which allow the investigation of key problems of policy and educational practice with non-traditional and multidimensional perspectives. The main LA research areas can be classified as follows: (i) definition of predictive models of the risk of insufficient or particularly positive school performance; (ii) profiling of student characteristics associated with specific behaviours / performances, and (iii) integrated assessment of educational / teaching practices capable of impacting students' results. In this session, theoretical, methodological and / or empirical contributions on the use of Learning Analytics approaches are invited, with reference to the main problems identified and with applications at any school level (primary, secondary and university).
Keywords: Learning Analytics, school performance, students’ characteristics.
INVALSI data: a tool for improving teaching and for evaluating transversal skills
Education is the basis of individual growth. Studying means to grow intellectually, to understand the world around us, to improve one's employment and economic condition and to become citizens capable of acting in complex social systems. Can INVALSI data trigger an improvement process linked to test results and to the evaluation of the transversal skills necessary to face reality outside school? The aim of the contributions presented in this session would be to establish a link between classroom practice and scientific research, to discuss teaching problems and perspectives, and to pave the way for an interdisciplinary debate.
Keywords: teaching practices, learning, educational research, technologies and tools in education, transversal skills, school.
Student results and their characteristics
The study of students’ characteristics (gender, socio-economic-cultural background, origin, etc.) allows highlighting the differences and similarities that have always characterized school results. The contributions presented in this session will promote the debate on the topic of school inclusion and may propose solution strategies for the gaps that currently exist.
Keywords: gender, socio-economic-cultural background, origin, gaps, school performance, inclusion.
Models and methods applied to INVALSI data
The purpose of a mathematical model is to represent a given object or phenomenon as incisively as possible and its aim is to make future prognoses on a system. INVALSI data are a large-scale source database for the implementation of these models. The contributions presented in this session will propose new solutions and perspectives for the analysis of the school system as a whole.
Keywords: mathematical model, methodologies, data, innovation, experimentation.
INVALSI data as a tool to support innovation and school improvement
Since 2015, the ‘Improvement Plan’ became part of the school agenda. The Improvement Plan is a path that entails transformations and changes in a dynamic approach involving the whole school community and affecting two dimensions: the didactic and the managerial/organizational. The works presented in this session, for which INVALSI data constitute a precious resource, will provide ideas for the self-reflection and self-assessment of individual schools.
Keywords: Evaluation, improvement, innovation, training, strategies, results, quality of the educational system, school effect.
CBT tests and learning analysis
Starting from 2017/2018 school year, computer based tests (CBT) have been introduced in national surveys and today these tools are used for school grades 8, 10 and 13. Also at international level, the tests of the various surveys managed by OECD and IEA are going in the same direction. Compared to paper&pencil, CBT opens new research scenarios. In which order have the items been completed? What responses have been reviewed and how have they been changed? How long did it take a student to answer each individual item? The works presented in this session could answer various questions and illustrate the potential of these tools.
Keywords: Computer based test, evaluation, digital teaching, didactic innovation, learning, effectiveness.
The role of teachers on student achievement
Scientific coordinator of the session: Gianluca Argentin, Università di Milano Bicocca
Teachers are known to be a crucial school factor that influences student achievement, but the mechanisms through which this process takes place are still largely obscure. This session encourages the presentation of papers focusing on characteristics, attitudes and practices of teachers and on analyses that evaluate (positively or negatively) the impacts on student performance and inequalities in education.
Keywords: teachers, teaching practices, school results.
Advanced Secondary Analysis of Large-scale Assessments in Education: A Discussion of Methods
Organizator: Andres Sandoval-Hernandez, University of Bath
An illustration of advanced methods for secondary data analysis (e.g. person-centered and variables-centered measurement models; multilevel/SEM models) applied to Italian and international large-scale assessment data and its complexities (e.g. sampling weights, plausible values, missing data).
Using Results of Secondary Analysis of Large-scale Assessments in Education to Inform Educational Policy
Organizator: Maria Magdalena Isac, KU Leuven & INVALSI
A didactic illustration of the use of results from large-scale assessment data in education to inform policy actors and wider audiences with examples of several policy briefs and the process of their elaboration.
Agenda 2030: survey on Sustainable Development Goals through INVALSI data.
This workshop will focus on 3 out of the 17 sustainable development goals (SDGs) adopted by all United Nations Member States in 2015. 1) Provide quality, fair and inclusive education; 2) achieve gender equality and empower all women and girls; 3) reduce economic inequalities within and outside the national borders. INVALSI datasets will provide the base to take a snapshot of the results achieved, which can stimulate a discussion about possible improvements and a starting point for measuring possible progress.
Interested parties must send an abstract (in Italian and English, maximum 6,000 characters including spaces for each) together with 3-6 keywords (in Italian and English) and a short biography (maximum 350 characters including spaces , in Italian and English) of each author / co-author.
Guidelines for abstracts' submission
For both the scientific research and the teaching tier, abstracts must summarize the entire work in order to allow readers to quickly get an idea of the contribution. Therefore they should be:
- accurate: the abstract should reflect the aims and content of the contribution. Do not include information that does not appear in the contribution;
- non-evaluative: must report data and not judge;
- coherent and legible: the language must be clear and concise; use verbs rather than equivalent nouns and the active form rather than the passive one.
In order to improve the evaluation, both abstracts must be prepared in the following format and using the following paragraph style:
- Introduction, which will help to clarify the work orientation by using references available in literature;
- Object and research hypothesis;
- Data used;
Guidelines for the presentation of final contributions
The complete contribution should be written in Times new roman 12, line spacing 1.5 and must not exceed 8,000 words, including the final bibliography. Bibliographical references must follow the APA (American Psychological Association) standards.
Contributions relating to a scientific research work must be displayed in English and accompanied by slides in English; contributions relating to a work on teaching must be displayed in Italian and accompanied by slides in Italian.
An anti-plagiarism software will be used to check the works.
The contributions presented at the Seminar, if not already published or in press, can be included in a volume with ISBN with the consent of the author and after a double-blind peer review.
August 7th, 2020
Start call for paper.
september 15th, 2020
Abstract presentation opening.
october 26th, 2020 november 2nd, 2020
Deadline abstract submission.
november 16th, 2020 november 23rd, 2020
Communication of accepted abstracts.
november 16th, 2020 november 24th - december 7th, 2020
december 18, 2020 december 22nd, 2020
Inizio registrazione partecipanti.
january 31st, 2021 february 15th, 2021
february 5th, 2021 12 marzo 2021 29 marzo 2021
Submission of the contribution.
february 15th, 2021
Esteemed keynote speakers will introduce the main themes of the conference.