The Relative Effectiveness of Teachers and Learning Software: Evidence from a Field Experiment in El Salvador

Konstantin Buechel, Martina Jakob, Daniel Steffen, Christoph Kuehnhanss and Aymo Brunetti

Diskussionsschriften from Universitaet Bern, Departement Volkswirtschaft

Abstract: This study provides novel evidence on the relative effectiveness of computer-assisted learning (CAL) software and traditional teaching. Based on a randomized controlled trial in Salvadoran primary schools, we evaluate three interventions that aim to improve learning outcomes in mathematics: (i) teacher-led classes, (ii) CAL classes monitored by a technical supervisor, and (iii) CAL classes instructed by a teacher. As all three interventions involve the same amount of additional mathematics lessons, we can directly compare the productivity of the three teaching methods. CAL lessons lead to larger improvements in students' mathematics skills than traditional teacher-centered classes. In addition, teachers add little to the e ectiveness of learning software. Overall, our results highlight the value of CAL approaches in an environment with poorly qualified teachers.

Keywords: computer-assisted learning; productivity in education; primary education; teacher content knowledge (search for similar items in EconPapers)
JEL-codes: C93 I21 J24 O15 (search for similar items in EconPapers)
Date: 2020-04
New Economics Papers: this item is included in nep-edu, nep-eff, nep-exp and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://repec.vwiit.ch/dp/dp2006.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ube:dpvwib:dp2006

Access Statistics for this paper

More papers in Diskussionsschriften from Universitaet Bern, Departement Volkswirtschaft Contact information at EDIRC.
Bibliographic data for series maintained by Franz Koelliker ().