2 Can Mobile Phones Improve Learning? Jenny Aker
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Evidence from Three Evaluations of Adult Education Programs
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2 Can Mobile Phones Improve Learning? Jenny Aker
- 1. Jenny C. Aker, Tu.s University and IFPRI Lessons from a Decade’s Research on Poverty: InnovaCon, Engagement and Impact Pretoria, South Africa March 16-‐18, 2016 Jenny C. Aker Can Mobile Phones Improve Learning? Evidence from Three Evalua<ons of Adult Educa<on Programs Mobile Phones and Adult EducaCon
- 2. Source: UN Human Development Report,2014 Educa<on in sub-‐Saharan Africa Jenny C. Aker Mobile Phones and Adult EducaCon 0 10 20 30 40 50 60 70 80 90 100 Botswana Nigeria Ghana Tanzania DRC Togo Central African Republic Ivory Coast Niger Mali
- 3. • How can educaConal outcomes be improved? • SubstanCal research on educaCon intervenCons provides evidence on what is effecCve in increasing school parCcipaCon o CondiConal and uncondiConal cash transfers, scholarships, deworming, informaCon • Yet evidence is mixed on how to improve learning in a cost-‐effecCve way o Number of evaluaCons have shown that spending on certain inputs has not increased test scores Mo<va<on Jenny C. Aker Mobile Phones and Adult EducaCon
- 4. Mobile Phone Adop<on in Africa Jenny C. Aker Mobile Phones and Adult EducaCon 16 25 37 52 82 135 200 279 376 455 515 620 754 802 895 -‐ 100 200 300 400 500 600 700 800 900 1,000 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Number of Subscribers (Millions) Total Number of Mobile Phone Subscribers in Sub-‐ Saharan Africa Source: Wireless Intelligence, Ericsson 2015, GSMA 2013
- 5. Research Goals • Can simple informaCon technology (ie, mobile phones) be used as an educa&onal input for low-‐ literate adults? o Does it improve learning and other welfare outcomes? o Is it cost effecCve? Research Ques<ons Jenny C. Aker Mobile Phones and Adult EducaCon
- 6. Source: Transparency InternaConal 2013 Teacher Absenteeism Jenny C. Aker Mobile Phones and Adult EducaCon 27% absenteeism in some African countries (TI 2013)
- 7. • In response to high teacher absenteeism, many governments have shi.ed to community teachers o Such teachers have short-‐term, flexible contracts and may be more easily monitored by the community • Monitoring teachers remains a significant challenge, especially in countries with high transport costs and weak insCtuCons Teacher Absenteeism Jenny C. Aker Mobile Phones and Adult EducaCon
- 8. Research Goals • Can simple informaCon technology (ie, mobile phones) be used as an educa&onal input for low-‐literate adults? o Does it improve learning and other welfare outcomes? o Is it cost effecCve? • Can simple mobile phones be used as a means to monitor teachers’ absenteeism and improve accountability? o Does this improve learning? o How does it compare with in-‐person monitoring? • Could mobile phones serve as a subs&tute for teachers for certain types of learning? • Three randomized control trials of adult educaCon programs in Niger and the US Research Ques<ons Jenny C. Aker Mobile Phones and Adult EducaCon
- 9. 9 Context Jenny C. Aker Mobile Phones and Adult EducaCon
- 10. • NGOs (Catholic Relief Services) and the Ministry provide ten months of adult educaCon classes over a two-‐year period • Held February through June of each year • Taught reading, wriCng and math skills in indigenous language (Hausa and Zarma) • 5 courses per week, three hours per day • Taught by community literacy teachers • Fi.y literacy parCcipants per village (25 men, 25 women) – separate classes by gender • Typically characterized low enrolment, high drop-‐out and rapid skills depreciaCon Jenny C. Aker Adult Educa<on Interven<ons: Niger Mobile Phones and Adult EducaCon
- 11. Bakin Birgi (Monday) Zinder (Thursday) Tanout (Friday) 65 km~2 min Niamey (Sunday) 20 km~1 hour 750 km~2 min Mobile Phones as an Educa<onal Tool? Jenny C. Aker Mobile Phones and Adult EducaCon
- 12. Alphabe(sa(on de Base par Cellulaire (ABC) Jenny C. Aker Mobile Phones and Adult EducaCon
- 13. • Students: o Learned where to find numbers and lejers on mobile phone handset o Learned how to make and receive a call o Learned how to send and read SMS o Were provided with access to shared mobile phones (5 people per mobile phone) worth about $USD 10 • ABC module started six weeks before the end of classes • No extra class Cme for students Jenny C. Aker The ABC Module Mobile Phones and Adult EducaCon
- 14. • 113 villages were randomly assigned to one of two intervenCons: • T1. Regular adult educaCon (non-‐ABC) • T2. Regular adult educaCon + ABC module (ABC) • No pure control group, so compares the relaCve impact of the ABC module on learning Research Design Jenny C. Aker Mobile Phones and Adult EducaCon
- 15. • Learning outcomes (wriCng and math test scores) • Household producCon, markeCng, migraCon • Mechanisms • Cost-‐effecCveness Impacts Jenny C. Aker Jenny C. Aker Mobile Phones and Adult EducaCon
- 16. Raw Writing Test Scores 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Baseline Five months Eleven months ABC Non-ABC Wri<ng Scores Jenny C. Aker Mobile Phones and Adult EducaCon
- 17. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Baseline Five months Eleven months ABC Non-ABC Raw Math Test Scores Math Scores Similar effects for men and women and younger and older learners Results persisted two years a.er the program Jenny C. Aker Mobile Phones and Adult EducaCon
- 18. • Do mobile phones allow students to pracCce more outside of class? Yes • Do mobile phones affect students’ effort within class? It depends on teacher quality. • Are teachers more likely to ajend classes because they are moCvated by the presence of technology? No. 18 Jenny C. Aker Why did learning improve? Mobile Phones and Adult EducaCon
- 19. • The program cost $USD 7 more per student as compared to the tradiConal adult educaCon program, but students had higher learning outcomes and earned more • But community teachers taught only 2/3 of contracted courses o Could mobile phones be used to improve teacher accountability? Jenny C. Aker Key Takeaways Mobile Phones and Adult EducaCon
- 20. • Agents made four weekly phone calls to the teacher, the village chief and two randomly-‐selected students over six weeks • Short script with five quesCons: o Was there a literacy course this week? o How many days per week? o How many hours per day? o How many students ajended? o Is there anything else you would like to share? • General feedback provided to CRS on a weekly basis o No formal sancCons for less than contracted effort and no follow-‐up visits in the short-‐term Mobile Monitoring Jenny C. Aker Mobile Phones and Adult EducaCon
- 21. • 160 villages in two regions were randomly assigned to one of three intervenCons: • T1. Adult Educa<on: TradiConal adult educaCon program • T2. Mobile Monitoring: Adult educaCon plus mobile monitoring • C: Comparison. No adult educaCon. 21 Research Design Jenny C. Aker Mobile Phones and Adult EducaCon
- 22. • The NGO is unable to obtain informaCon about the teachers’ effort o High costs of supervision • If teachers believe they may be fired or penalized, addiConal monitoring should increase teachers’ effort and student learning • Yet monitoring could fail if wages are not high enough or it crowds out intrinsic moCvaCon 22 How would this affect learning? Jenny C. Aker Mobile Phones and Adult EducaCon
- 23. • Learning outcomes (EGRA/EGMA Reading and Math Tests) • Self-‐Efficacy and Self-‐Esteem • Household welfare • Mechanisms 23 Impacts Jenny C. Aker Mobile Phones and Adult EducaCon
- 24. Jenny C. Aker Mobile Phones and Adult EducaCon Reading Z-‐Scores 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Lejers Syllables Words Phrases Reading Z-‐Score Non-‐Monitoring Monitoring Similar results for math Different effects by teacher’s “alternaCve opCon”
- 25. “These calls prevent us from missing courses.” “Someone who works must be ‘controlled’”. “I felt closer to the hierarchy and wanted to do well.” “This proves that our work is important.” “It gave me courage.” Why did this improve learning? Jenny C. Aker Mobile Phones and Adult EducaCon
- 26. • Teachers o Do monitoring teachers teach more? A bit. o Are monitoring teachers more moCvated? Yes. o Were they more likely to be fired? No. • Student o Are students less likely to drop out? No. o Are students more moCvated? Yes. Why did this improve learning? Jenny C. Aker Mobile Phones and Adult EducaCon
- 27. Cost Effec<veness $0.00 $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 Mobile Monitoring In-‐Person Monitoring Staff Cme Call credit Gas Jenny C. Aker Mobile Phones and Adult EducaCon
- 28. • Mobile monitoring increased student learning by 20-‐50% o Will this be sustained if scaled? • Less costly than in-‐person monitoring o In-‐person monitoring was very light in this context • Why? Changes in teacher and student moCvaCon • Can mobile phones be used in other ways to support teachers? (Ie, pedagogy) • Can they be used as subsCtutes for teachers in areas where condiCons are difficult (ie, conflicts)? 28 Key Takeaways Jenny C. Aker Mobile Phones and Adult EducaCon
- 29. • Mobile phone-‐based adult educaCon curriculum using a simple mobile phone o Series of 400 micro-‐modules via audio, calls and SMS • Piloted in Spanish in Los Angeles with low-‐literate learners • Students increased their reading levels by two years over a four-‐month period • Caveats: Small sample size, high drop-‐out rates 29 The CellEd Program Jenny C. Aker Mobile Phones and Adult EducaCon
- 30. • Can mobile phones be used as an educaConal tool? • Evidence is mixed for ICT and children’s educaConal outcomes in general, but research in Niger suggests it can lead to sustained learning outcomes for adults • Depends upon the type of ICT and how the ICT is incorporated into the learning curriculum • ICT can be either a complement or subsCtute for teacher quality • Less evidence of the impact of adult educaCon programs on household welfare and children’s educaConal outcomes o Currently measuring these impacts in Niger 30 The BoVom Line Jenny C. Aker Mobile Phones and Adult EducaCon
- 31. 31 Jenny C. Aker Mobile Phones and Adult EducaCon Thank you
- 32. 32 Thank you
- 33. Source: Evans and Ghosh (2008) 0 5 10 15 20 25 30 35 40 45 50 Blackboards -‐ Ghana Furniture -‐ Philippines Teacher training -‐ Honduras Workbooks -‐ Philippines Remedial EducaCon (tutors) -‐ India CapitaCon grant -‐ Uganda Mobile phone module wriCng -‐ Niger Mobile phone module math -‐ Niger Classroom repair -‐ Ghana AddiConal teachers with tracking -‐ Kenya Girls' scholarship -‐ Kenya Teacher incenCves -‐ India Teacher incenCves -‐ Kenya Textbooks -‐ Kenya Remedial EducaCon -‐ India Preschool -‐ Philippines Class size reducCon -‐ Honduras EducaConal vouchers-‐Colombia Cost ($USD) per .1 s.d. increase in test scores How does this compare to other interven<ons? Cost per .1 s.d. increase
- 34. • 70% of teachers thought the calls were from CRS, 29% from the Ministry • 80% of teachers knew the village chief was called, 77% knew the students were called • High intra-‐village correlaCon of responses, even if courses were not held o Within-‐village correlaCons do not appear to change over Cme o Collusion or high degree of informaCon-‐sharing? Mobile Monitoring Experiment Aker and Ksoll Mobile Monitoring Works
- 35. Approche de Recherche 35 DFAP Villages 500 Outside evaluation Part of evaluation (160 villages) Random Assignment ABC Normal Monitoring (70) Pure control (20) Non-ABC Mobile Monitoring (70) ABC Non-ABC Experimental Design Aker and Ksoll Mobile Monitoring Works 2014 and 2015 2016 Geographic straCficaCon
- 36. Jenny C. Aker Mobile Phones and Adult EducaCon Math Z-‐Scores 0 0.1 0.2 0.3 0.4 0.5 0.6 # IdenCficaCon QuanCty Comparison Add/Subtract MulCply/Divide Math Z-‐Score Non-‐Monitoring Monitoring
- 37. • Geography: o The effects are primarily driven by one region -‐ where the costs of in-‐person monitoring are higher • Gender: o Stronger monitoring effects on men’s reading scores • Teacher characterisCcs: o Stronger monitoring effects for literacy teachers with a lower outside opCon (gender, educaCon, experience) o Stronger effects when teachers know the chief was called Heterogeneous effects Jenny C. Aker Mobile Phones and Adult EducaCon