Identify and Reduce Academic Dropout

Gati Itamar, HUJI, Faculty of Social Sciences, Psychology
Phillips-Berenstein Michal, HUJI, School of Education




Personal Wellbeing, Academic Performance



Academic dropout is a major global concern because of the detrimental consequences it has on the individual, institutions, and society as a whole. Despite the high percentage of those applying for higher education across the globe, about 30% of undergraduate students both in Israel (CBS, 2017), and the OECD (OECD, 2013) fail to complete their studies within 6 years on average. The dropout rate from the first year stands at 8.7 % on average, ranging from 13.7% in teaching colleges to 7.4% in universities. The dropout rate from the first year in the US has reached between 29%-35% (ACT, 2018).

Academic dropout causes a direct economic loss for the educational institution which loses tuition fees from already enrolled students.

Our Innovation

Prof. Gati has developed a validated system to identify students who are at high risk of dropping out. The early identification system can be used to alert relevant stakeholders to these students. The system comprises of a set of questionnaires, assessment algorithms and an intervention plan.

A set of short questionnaires examines the psycho-social metrics of students and assess their capability to deal with academic challenges. Individual feedback is offered to every student. The educational institution can then target intervention programs to these identified individuals.

The questionnaires relate to the major reasons for academic dropout such as:

  • Readiness for academic studies including previous knowledge and academic achievements.
  • Socio-demographic variables such as gender, socio-economic status, educational level in the family.
  • Socio-psychological variables including a variety of psychological aspects, attitudes, perceptions, and behaviors that help people to deal with a challenge of successful integration into academic studies.


Prof. Gati’s method was tested on over 10,000 students in 7 cycles, and in various population groups. The method was found effective in precise identification and prediction of students who are at risk of academic dropout.

The rollout of this method in educational institutions will help to preserve students and provide targeted support to those in need.


Contact for more information:

Anna Pellivert
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