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Posts Tagged ‘learning’

Modified from the original, posted on the MERL Tech Blog, July 20, 2020

For the past six years, I’ve been organizing the MERL Tech conference and related activities. We cancelled this year’s conference (planned for Johannesburg in September) because of coronavirus, but plenty has been happening despite the fact that we can’t gather in person.

One project I’m happy to launch today is the State of the Field of MERL Tech research, which pulls together lessons from five years of convening hundreds of monitoring, evaluation, research, and learning (MERL) and technology practitioners who have joined us as part of the MERL Tech community.

These four new papers build on research that Michael Bamberger and I co-authored in 2014, which aimed to set the stage and begin framing this (then) emerging field. For this latest research, we started by examining the evolution of the field since 2014 and plotting three waves of MERL Tech (as described below) onto Gartner’s Hype Cycle. Each of the waves is explored further in its own paper.

Three waves of MERL Tech explored in the State of the Field series.

Now is a good time to take stock of the past, given that 2020 marks a turning point in many ways. The world is in the midst of the COVID-19 pandemic, and there is an urgent need to know what is happening, where, and to what extent. Data is a critical piece of the COVID-19 response — it can mean the difference between life and death — but data collection, use, and sharing can also invade privacy or cause harm now or in the future. As technology use grows due to stay-at-home orders and a push for “remote monitoring” and “remote program delivery” so, too, does the amount of data captured and shared.

At the same time, we’re witnessing (and I hope, also joining in with) a global call for justice — perhaps a tipping point — in the wake of decades of racist and colonialist systems that operate at the level of nations, institutions, organizations, global aid and development, and the tech sector. There is no denying that these power dynamics and systems have shaped the MERL space as a whole, including the MERL Tech space.

Moments of crisis test a field, and we live in extreme times. The coming decade will demand a nimble, adaptive, fair, and just use of data for managing complexity and for gaining longer-term understanding of change and impact. The sector, its relationships, and its power dynamics will need a fundamental re-shaping.

It is in this time of upheaval and change that we are releasing four papers covering the field from 2014-2019 as a launchpad for thinking about the future of MERL Tech. In September 2018, the papers’ authors began reviewing the past five years of MERL Tech events to identify lessons, trends, and issues in this rapidly changing field. They also reviewed the literature base in an effort to determine what we know about technology in MERL, what we yet need to understand, and what are the gaps in the formal literature. No longer is this a nascent field, yet it is one that is hard to keep up with, due to its fast pace and constant shifts. We have learned many lessons over the past five years, but complex political, technical, and ethical questions remain.

Can the wider MERL Tech community take action to make the next phase of MERL Tech development effective, responsible, ethical, just, and equitable? We share these papers as conversation pieces and hope they will generate more discussion in the MERL Tech space about where to go from here.

The State of the Field series includes four papers:

MERL Tech State of the Field: The Evolution of MERL Tech: Linda Raftree, independent consultant and MERL Tech Conference organizer.

What We Know About Traditional MERL Tech: Insights from a Scoping Review: Zach Tilton, Michael Harnar, and Michele Behr, University of Western Michigan; Soham Banerji and Manon McGuigan, independent consultants; and Paul Perrin, Gretchen Bruening, John Gordley and Hannah Foster, University of Notre Dame; Linda Raftree, independent consultant and MERL Tech Conference organizer.

Big Data to Data Science: Moving from “What” to “How” in the MERL Tech SpaceKecia Bertermann, Luminate; Alexandra Robinson, Threshold.World; Michael Bamberger, independent consultant; Grace Lyn Higdon, Institute of Development Studies; Linda Raftree, independent consultant and MERL Tech Conference organizer.

Emerging Technologies and Approaches in Monitoring, Evaluation, Research, and Learning for International Development Programs: Kerry Bruce and Joris Vandelanotte, Clear Outcomes; and Valentine Gandhi, The Development CAFE and Social Impact.

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(Reposting, original appears here)

Back in 2014, the humanitarian and development sectors were in the heyday of excitement over innovation and Information and Communication Technologies for Development (ICT4D). The role of ICTs specifically for monitoring, evaluation, research and learning (aka “MERL Tech“) had not been systematized (as far as I know), and it was unclear whether there actually was “a field.” I had the privilege of writing a discussion paper with Michael Bamberger to explore how and why new technologies were being tested and used in the different steps of a traditional planning, monitoring and evaluation cycle. (See graphic 1 below, from our paper).

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The approaches highlighted in 2014 focused on mobile phones, for example: text messages (SMS), mobile data gathering, use of mobiles for photos and recording, mapping with specific handheld global positioning systems (GPS) devices or GPS installed in mobile phones. Promising technologies included tablets, which were only beginning to be used for M&E; “the cloud,” which enabled easier updating of software and applications; remote sensing and satellite imagery, dashboards, and online software that helped evaluators do their work more easily. Social media was also really taking off in 2014. It was seen as a potential way to monitor discussions among program participants, gather feedback from program participants, and considered an underutilized tool for greater dissemination of evaluation results and learning. Real-time data and big data and feedback loops were emerging as ways that program monitoring could be improved, and quicker adaptation could happen.

In our paper, we outlined five main challenges for the use of ICTs for M&E: selectivity bias; technology- or tool-driven M&E processes; over-reliance on digital data and remotely collected data; low institutional capacity and resistance to change; and privacy and protection. We also suggested key areas to consider when integrating ICTs into M&E: quality M&E planning, design validity; value-add (or not) of ICTs; using the right combination of tools; adapting and testing new processes before role-out; technology access and inclusion; motivation to use ICTs, privacy and protection; unintended consequences; local capacity; measuring what matters (not just what the tech allows you to measure); and effectively using and sharing M&E information and learning.

We concluded that:

  • The field of ICTs in M&E is emerging and activity is happening at multiple levels and with a wide range of tools and approaches and actors. 
  • The field needs more documentation on the utility and impact of ICTs for M&E. 
  • Pressure to show impact may open up space for testing new M&E approaches. 
  • A number of pitfalls need to be avoided when designing an evaluation plan that involves ICTs. 
  • Investment in the development, application and evaluation of new M&E methods could help evaluators and organizations adapt their approaches throughout the entire program cycle, making them more flexible and adjusted to the complex environments in which development initiatives and M&E take place.

Where are we now:  MERL Tech in 2019

Much has happened globally over the past five years in the wider field of technology, communications, infrastructure, and society, and these changes have influenced the MERL Tech space. Our 2014 focus on basic mobile phones, SMS, mobile surveys, mapping, and crowdsourcing might now appear quaint, considering that worldwide access to smartphones and the Internet has expanded beyond the expectations of many. We know that access is not evenly distributed, but the fact that more and more people are getting online cannot be disputed. Some MERL practitioners are using advanced artificial intelligence, machine learning, biometrics, and sentiment analysis in their work. And as smartphone and Internet use continue to grow, more data will be produced by people around the world. The way that MERL practitioners access and use data will likely continue to shift, and the composition of MERL teams and their required skillsets will also change.

The excitement over innovation and new technologies seen in 2014 could also be seen as naive, however, considering some of the negative consequences that have emerged, for example social media inspired violence (such as that in Myanmar), election and political interference through the Internet, misinformation and disinformation, and the race to the bottom through the online “gig economy.”

In this changing context, a team of MERL Tech practitioners (both enthusiasts and skeptics) embarked on a second round of research in order to try to provide an updated “State of the Field” for MERL Tech that looks at changes in the space between 2014 and 2019.

Based on MERL Tech conferences and wider conversations in the MERL Tech space, we identified three general waves of technology emergence in MERL:

  • First wave: Tech for Traditional MERL: Use of technology (including mobile phones, satellites, and increasingly sophisticated data bases) to do ‘what we’ve always done,’ with a focus on digital data collection and management. For these uses of “MERL Tech” there is a growing evidence base. 
  • Second wave:  Big Data. Exploration of big data and data science for MERL purposes. While plenty has been written about big data for other sectors, the literature on the use of big data and data science for MERL is somewhat limited, and it is more focused on potential than actual use. 
  • Third wave:  Emerging approaches. Technologies and approaches that generate new sources and forms of data; offer different modalities of data collection; provide ways to store and organize data, and provide new techniques for data processing and analysis. The potential of these has been explored, but there seems to be little evidence base to be found on their actual use for MERL. 

We’ll be doing a few sessions at the American Evaluation Association conference this week to share what we’ve been finding in our research. Please join us if you’ll be attending the conference!

Session Details:

Thursday, Nov 14, 2.45-3.30pm: Room CC101D

Friday, Nov 15, 3.30-4.15pm: Room CC101D

Saturday, Nov 16, 10.15-11am. Room CC200DE

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(I’ve been blogging a little bit over at MERLTech.org. Here’s a repost.)

It can be overwhelming to get your head around all the different kinds of data and the various approaches to collecting or finding data for development and humanitarian monitoring, evaluation, research and learning (MERL).

Though there are many ways of categorizing data, lately I find myself conceptually organizing data streams into four general buckets when thinking about MERL in the aid and development space:

  1. ‘Traditional’ data. How we’ve been doing things for(pretty much)ever. Researchers, evaluators and/or enumerators are in relative control of the process. They design a specific questionnaire or a data gathering process and go out and collect qualitative or quantitative data; they send out a survey and request feedback; they do focus group discussions or interviews; or they collect data on paper and eventually digitize the data for analysis and decision-making. Increasingly, we’re using digital tools for all of these processes, but they are still quite traditional approaches (and there is nothing wrong with traditional!).
  2. ‘Found’ data.  The Internet, digital data and open data have made it lots easier to find, share, and re-use datasets collected by others, whether this is internally in our own organizations, with partners or just in general. These tend to be datasets collected in traditional ways, such as government or agency data sets. In cases where the datasets are digitized and have proper descriptions, clear provenance, consent has been obtained for use/re-use, and care has been taken to de-identify them, they can eliminate the need to collect the same data over again. Data hubs are springing up that aim to collect and organize these data sets to make them easier to find and use.
  3. ‘Seamless’ data. Development and humanitarian agencies are increasingly using digital applications and platforms in their work — whether bespoke or commercially available ones. Data generated by users of these platforms can provide insights that help answer specific questions about their behaviors, and the data is not limited to quantitative data. This data is normally used to improve applications and platform experiences, interfaces, content, etc. but it can also provide clues into a host of other online and offline behaviors, including knowledge, attitudes, and practices. One cautionary note is that because this data is collected seamlessly, users of these tools and platforms may not realize that they are generating data or understand the degree to which their behaviors are being tracked and used for MERL purposes (even if they’ve checked “I agree” to the terms and conditions). This has big implications for privacy that organizations should think about, especially as new regulations are being developed such a the EU’s General Data Protection Regulations (GDPR). The commercial sector is great at this type of data analysis, but the development set are only just starting to get more sophisticated at it.
  4. ‘Big’ data. In addition to data generated ‘seamlessly’ by platforms and applications, there are also ‘big data’ and data that exists on the Internet that can be ‘harvested’ if one only knows how. The term ‘Big data’ describes the application of analytical techniques to search, aggregate, and cross-reference large data sets in order to develop intelligence and insights. (See this post for a good overview of big data and some of the associated challenges and concerns). Data harvesting is a term used for the process of finding and turning ‘unstructured’ content (message boards, a webpage, a PDF file, Tweets, videos, comments), into ‘semi-structured’ data so that it can then be analyzed. (Estimates are that 90 percent of the data on the Internet exists as unstructured content). Currently, big data seems to be more apt for predictive modeling than for looking backward at how well a program performed or what impact it had. Development and humanitarian organizations (self included) are only just starting to better understand concepts around big data how it might be used for MERL. (This is a useful primer).

Thinking about these four buckets of data can help MERL practitioners to identify data sources and how they might complement one another in a MERL plan. Categorizing them as such can also help to map out how the different kinds of data will be responsibly collected/found/harvested, stored, shared, used, and maintained/ retained/ destroyed. Each type of data also has certain implications in terms of privacy, consent and use/re-use and how it is stored and protected. Planning for the use of different data sources and types can also help organizations choose the data management systems needed and identify the resources, capacities and skill sets required (or needing to be acquired) for modern MERL.

Organizations and evaluators are increasingly comfortable using mobile and/or tablets to do traditional data gathering, but they often are not using ‘found’ datasets. This may be because these datasets are not very ‘find-able,’ because organizations are not creating them, re-using data is not a common practice for them, the data are of questionable quality/integrity, there are no descriptors, or a variety of other reasons.

The use of ‘seamless’ data is something that development and humanitarian agencies might want to get better at. Even though large swaths of the populations that we work with are not yet online, this is changing. And if we are using digital tools and applications in our work, we shouldn’t let that data go to waste if it can help us improve our services or better understand the impact and value of the programs we are implementing. (At the very least, we had better understand what seamless data the tools, applications and platforms we’re using are collecting so that we can manage data privacy and security of our users and ensure they are not being violated by third parties!)

Big data is also new to the development sector, and there may be good reason it is not yet widely used. Many of the populations we are working with are not producing much data — though this is also changing as digital financial services and mobile phone use has become almost universal and the use of smart phones is on the rise. Normally organizations require new knowledge, skills, partnerships and tools to access and use existing big data sets or to do any data harvesting. Some say that big data along with ‘seamless’ data will one day replace our current form of MERL. As artificial intelligence and machine learning advance, who knows… (and it’s not only MERL practitioners who will be out of a job –but that’s a conversation for another time!)

Not every organization needs to be using all four of these kinds of data, but we should at least be aware that they are out there and consider whether they are of use to our MERL efforts, depending on what our programs look like, who we are working with, and what kind of MERL we are tasked with.

I’m curious how other people conceptualize their buckets of data, and where I’ve missed something or defined these buckets erroneously…. Thoughts?

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Screen Shot 2016-01-12 at 10.17.25 AMSince I started looking at the role of ICTs in monitoring and evaluation a few years back, one concern that has consistently come up is: “Are we getting too focused on quantitative M&E because ICTs are more suited to gather quantitative data? Are we forgetting the importance of qualitative data and information? How can we use ICTs for qualitative M&E?”

So it’s great to see that Insight Share (in collaboration with UNICEF) has just put out a new guide for facilitators on using Participatory Video (PV) and the Most Significant Change (MSC) methodologies together.

 

The Most Significant Change methodology is a qualitative method developed (and documented in a guide in 2005) by Rick Davies and Jess Dart (described below):

Screen Shot 2016-01-12 at 9.59.32 AM

Participatory Video methodologies have also been around for quite a while, and they are nicely laid out in Insight Share’s Participatory Video Handbook, which I’ve relied on in the past to guide youth participatory video work. With mobile video becoming more and more common, and editing tools getting increasingly simple, it’s now easier to integrate video into community processes than it has been in the past.

Screen Shot 2016-01-12 at 10.00.54 AM

The new toolkit combines these two methods and provides guidance for evaluators, development workers, facilitators, participatory video practitioners, M&E staff and others who are interested in learning how to use participatory video as a tool for qualitative evaluation via MSC. The toolkit takes users through a nicely designed, step-by-step process to planning, implementing, interpreting and sharing results.

I highly recommend taking a quick look at the toolkit to see if it might be a useful method of qualitative M&E — enhanced and livened up a bit with video!

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Screen Shot 2015-09-02 at 7.38.45 PMBack in 2010, I wrote a post called “Where’s the ICT4D distance learning?” which lead to some interesting discussions, including with the folks over at TechChange, who were just getting started out. We ended up co-hosting a Twitter chat (summarized here) and having some great discussions on the lack of opportunities for humanitarian and development practitioners to professionalize their understanding of ICTs in their work.

It’s pretty cool today, then, to see that in addition to having run a bunch of on-line short courses focused on technology and various aspects of development and social change work, TechChange is kicking off their first Diploma program focusing on using ICT for monitoring and evaluation — an area that has become increasingly critical over the past few years.

I’ve participated in a couple of these short courses, and what I like about them is that they are not boring one-way lectures. Though you are studying at a distance, you don’t feel like you’re alone. There are variations on the type and length of the educational materials including short and long readings, videos, live chats and discussions with fellow students and experts, and smaller working groups. The team and platform do a good job of providing varied pedagogical approaches for different learning styles.

The new Diploma in ICT and M&E program has tracks for working professionals (launching in September of 2015) and prospective Graduate Students (launching in January 2016). Both offer a combination of in-person workshops, weekly office hours, a library of interactive on-demand courses, access to an annual conference, and more. (Disclaimer – you might see some of my blog posts and publications there).

The graduate student track will also have a capstone project, portfolio development support, one-on-one mentorship, live simulations, and a job placement component. Both courses take 16 weeks of study, but these can be spread out over a whole year to provide maximum flexibility.

For many of us working in the humanitarian and development sectors, work schedules and frequent travel make it difficult to access formal higher-level schooling. Not to mention, few universities offer courses related to ICTs and development. The idea of incurring a huge debt is also off-putting for a lot of folks (including me!). I’m really happy to see good quality, flexible options for on-line learning that can improve how we do our work and that also provides the additional motivation of a diploma certificate.

You can find out more about the Diploma program on the TechChange website  (note: registration for the fall course ends September 11th).

 

 

 

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Cameroon - realizing phone takes videoI had the chance to share some thoughts at UNESCO’s recent Mobile Learning Week. My presentation explored some myths about girls empowerment and mobile learning and offered suggestions of things to think about when designing and implementing programs. Ideas for the presentation were drawn from research and practitioner experiences (mine and those of others that I’ve talked with and worked with over the past few years). Here’s what I talked about below. Since realities are subjective and complex, and contexts differ immensely around the world, I’m putting these out mainly as discussion starters. Some seem super obvious and some contradict each other (which may speak to the point that there is no universal truth!), so I’m curious to know what other people think…

Myth 1: Mobile as a stand-alone solution.

Reality: The mobile phone is just one part of the informational and cultural ecosystem. There is a lot of hype about mobile. I think as a sector we are mostly past the idea of mobile as a stand-alone solution, but in case not, it’s the first myth I’d challenge. There is not a lot that a mobile phone can do as a stand-alone tool to empower girls or improve their education and learning. 

Things to consider: The mobile phone is the device that is most likely to already be in the hands of your target user — but the possibilities and channels don’t start and end with mobile phones. It’s important to think of the mobile phone as just one part of a much wider informational, social, cultural and educational ecosystem and see where it might fit in to support girls’ learning. It’s likely that mobile phones will be used more outside of the classroom than in – in my experience, I’ve found that schools often don’t allow mobiles to be brought into class. So, it’s more about integrating mobiles as a tool that supports rather than as the sole channel for learning and information sharing.

Myth 2: It’s the technology that’s mobile.

Reality: In most cases, the learner is mobile, too. This is one of the exciting things about technology and learning. It’s something I heard John Traxler say a few years ago, and I thought it was really smart. John said we should really be thinking about mobile learners, not just mobile technology. Learners access and share information in all kinds of ways, at different locations, using different devices or not using devices at all.

Things to consider: Rather than starting with the mobile phone, think about design based on a clear understanding of ’digital repertoires’ – in other words, user behaviors or patterns that span places and devices based on factors like data capacity, cost, purpose. These repertoires will differ according to culture, sex, economic status, and availability of information points and sources. For example, maybe some girls use Google search to do homework at an Internet café but use their own phone or a borrowed phone for quick, short text reminders or questions to friends about schoolwork. Maybe other girls are not allowed to go to Internet cafés or they feel uncomfortable doing so, and they rely more on their mobile phone and their friends. This was the case in one community near Jakarta that I was in last month. One of the girls talked about her 15-year-old friend:

 

“She’s too shy to go to the Internet shop…. Boys are always sitting out, calling you to ask ‘where are you going?’ or whistling. She feels too embarrassed to go into the shop because everyone will look at her.”

In a consultation conducted by Plan in 2011, girls in some countries said it was too dangerous to travel to the Internet café, especially at night. When men and boys watch porn and play video games in Internet cafes, girls tend to feel quite uncomfortable. Libraries, if available, may be places where girls go to access Internet because they feel safer. Girls may face reputation risk if they go too often to the Internet café. So in this case, girls may rely on phones. In some parts of East and West Africa, however, girls with mobile phones may be accused of having ‘sugar daddies’ or selling sex for airtime or nice phones, so the phone also carries reputation risk. All of these situations impact on girls’ communication repertoires, and program designers need to take them into consideration. And perhaps most importantly, ‘girls’ are not a homogeneous group so we always need to unpack which girls, where, when, what, at what age, living where, with what kinds of social or cultural restrictions, etc.

Myth 3: Vulnerable girls don’t have access to mobiles.

Reality: Many girls with phones are more vulnerable than we think, and more girls that we consider vulnerable are accessing mobiles. This is something that Colman Chamberlain from the Girl Effect’s mobile initiative pointed out. “We often hear that the most vulnerable girls don’t have access to mobile phones,” he says, “but this depends on how we understand and define vulnerability. Many girls with phones are vulnerable, and many vulnerable girls are starting to access mobile. This means we have a real chance to reach and engage with them.”

Things to consider: Age does normally play a role in access to mobiles. Younger girls from lower income families in most countries do not have their own mobile phones. Upper class children may, however, have phones. It really varies. Recent research (unpublished) found that it was common for 14-15 yr olds in Indonesia to have their own phones. In India and Bangladesh, that age was closer to 18. Girls who were no longer in school often had a mobile — some had even dropped out to get jobs in order to purchase a mobile. Sometimes married girls’ husbands purchase them a phone, yet it may be primarily to control and monitor their whereabouts.

When designing programs, it’s really important to take the time to learn whether the girls you’d like to work with own or borrow mobile phones and whether their access is controlled by someone else or if they are free to use a mobile however they’d like. Design for different scenarios and ‘user repertoires’ based on girls’ access and use habits. Don’t make assumptions on which girls access mobiles for what and how based on perceived vulnerability, do the research and you may be surprised when you get into the weeds.

Myth 4: Cost is the biggest barrier to girls’ mobile phone access and use. 

Reality: Cost is a barrier, but perhaps not the biggest one. Clearly cost is still a big barrier for the poorest girls. But the unwillingness to invest in a girl’s access to mobile or to information and learning is linked to other aspects like a girl’s position in her family or society. Mobiles are also becoming cheaper, so the cost barrier has been reduced in some ways. Overall, compared to landlines, as Katie Ramsay at Plan Australia notes, mobile is cheaper and that opens up access to information for even the poorest families.

Research conducted this past year in India, Bangladesh and Indonesia, found that in some communities girls have much greater access than assumed, and cost was a lower barrier than originally thought. Parents and gatekeepers were actually a bigger barrier in some countries. For many of us this is a total no-brainer, but I still think it’s worth bringing up.

Things to consider: As already mentioned, the key when developing programs is to dig deep and talk with girls directly to understand and help them to overcome different barriers, whether those are personal, familiar, economic, societal or institutional.

In order to help get past these barriers, mobile-enabled programming or product/service offerings need to have real value to girls as well as their gatekeepers, so that girls’ participation in programs and use of mobiles is seen by gatekeepers as positive. This was shown clearly in a UNESCO girls’ literacy program in Pakistan, where 87% of parents changed from a negative opinion about girls using a mobile phone to a positive perspective by the end of the program, because they saw the utility of the phone for girls’ literacy.

It’s important to do work on educating and changing behaviors of parents. Katie Ramsay also notes that in places where men own the tech, there is a huge opportunity for targeting them to gain their support for girls’ education. So it’s worth re-thinking the role of mobiles in girl-focused programs, especially where girls’ access to mobile is low or controlled. The best use of mobiles for learning may not be ‘delivering content’ to girls via a mobile device. Instead it might be using mobile and other media to target gatekeepers to change their behavior and beliefs around girls’ education and girls’ empowerment.

Myth 5: Girls share their phones.

Reality: Phone sharing brings with it a challenging social power dynamic. Many people in ‘the West’ hold the romantic notion that people in ‘developing countries’ like to share everything and live communally. Now, I’m not saying that girls are not generous, but when it comes to girls and phones, we have not really seen a great desire to share.

In some of the unpublished research conducted in Asia (and previously referenced in this post), girls without phones said that they do borrow phones, often from family members or friends, but they don’t necessarily like doing so. They said that borrowing here and there just isn’t enough to do anything substantial on a phone. Girls described girls who do not have mobile phones as sad and unpopular. They drew girls with phones as happy, popular, and successful. Some girls also described girls with phones as stuck up and selfish and said that girls who have phones don’t share them with girls that don’t have phones.

 

“A girl with a phone would look down on me, and show off what her phone does. She would let me hold it, but only because she would like to take it back from me again.” —Girl, 18, Dhaka

I was at a school in Cameroon last year, when a big fight broke out because one girl had taken another girl’s phone and thrown it in the toilet. The professor said that fighting over mobile phones was common among students. Phones had been prohibited at school in part to reduce conflicts, and sometimes students ratted each other out for having phones at school. This is not specifically a “mobile phone” problem, it’s a wealth or class or equity issue, but it manifests itself with phones because they are an asset that defines haves and have-nots. 

Things to consider: Don’t assume it’s easy for girls to borrow phones. If you find that many of your targeted users for a mobile-enabled initiative are borrowers, then it’s important to design short, to-the-point options for them, because they may have only a few minutes at a time with a mobile. Girls may not share their phones unless there is some kind of incentive for doing so. If you are designing for borrowers, think about rapid communication in bursts, and don’t communicate about anything that would put a girl at social or reputation risk if the person she borrows the phone from should see it.

Myth 6: All girls (& all youth) are tech savvy.

Reality: Many girls are indeed tech savvy, but some are still behind the curve. In many places, girls with phones are way more tech savvy than their parents. And most young people around the world are pretty quick to pick up on technology. But girls’ level of savvy will obviously depend on what they have access to.

Girls I talked with in the urban slums areas of Jakarta were quite tech-adept and had Internet-ready phones, but they still only used Facebook and Google. They also mixed up ‘Facebook’ and ‘Google’ with ‘The Internet’ and did not use email. They were unfamiliar with the concept of an “app”. Girls knew how to search for jobs online (via Google), but they said they had trouble understanding how to fill out online forms to apply for those jobs. So regardless of a girl’s level of tech savvy, in this case, she was still missing certain skills and relevant online content that would have helped her get to the next level of job-seeking.

Things to consider: It’s really important to do your research to understand what technologies and platforms girls are familiar with and be sure to plan for how to engage girls with those that they are unfamiliar with. Basic literacy might also still be a huge issue among adolescent girls in some places.

Basically, the message here again is to avoid making assumptions, to do your research, and to remember that girls are not a homogeneous group. Market research techniques can be helpful to really start understanding nuances regarding which girls do what, where and how on a mobile device.

Myth 7: Girls don’t have time to use mobile phones.

Reality: You might be surprised by which girls find time to spend on a mobile phone. This again really depends on which girls, and where! Girls find the time to use mobile, even if it’s not at the always on-line levels that we find in places like the US and Europe, notes Colman from Girl Effect. Spending time in the communities you’re working with can allow you to find times that girls have free and uncontrolled access. Jessica Heinzelman from DAI told us that in one project she was working on, they had assumed that girls in more traditional communities and rural geographies would have less access to mobiles. In reality, it was common for girls to be sent on errands with mobiles to places where there was connectivity to contact relatives on behalf of the family, leaving the girls with at least some alone time with the mobile.

Schoolgirls in the slum area of Jakarta that I worked in earlier this year said they checked their Facebook every day. Out of school urban girls checked at least a few times per week, and rural out of school girls also usually managed to borrow a phone to check Facebook quickly now and then.

Things to consider: I’m beating the drum again here about the importance of on-the-ground research and user testing to find out what is happening in a particular context. Alexandra Tyers from GSMA points out that user testing is really a critical piece of any girls and mobile learning effort, and that it can actually be done for a reasonable price. She notes that in her case, “Bangladesh user testing cost $5,000 USD for fifty tests in five different locations around the country. And yet the return on investment by making those necessary changes is likely to be large because making sure the product is right will ensure easy adoption and maximum uptake.”

Myth 8: Mobile phones can’t address girls’ real needs.

Reality: Mobile phones can help address girls’ real needs, but probably not as stand-alone devices, and maybe not as ‘content delivery’ channels. There is a lot of hype around mobile learning and mEducation, and as some presenters talked about at Mobile Learning Week, there is little evidence to help us know how to integrate mobiles in ways that could scale (where appropriate) and offer real results. I sometimes think this is because we are expecting mobile and ICTs in general to do more than they feasibly can.

Depending on the context and situation, where I have seen the greatest opportunity for mobiles is:

  • enabling girls to connect with peers and information
  • allowing girls more opportunities for voicing their opinions
  • linking girls to online support and services
  • linking girls with offline support and services.
  • helping organizations to track and monitor their programs (and hopefully then do a better job of adapting them to girls’ real needs).

Things to consider: It’s really important to think through what the best role for mobile is (if any role at all). Here is where you can (and should) be super creative. You may not get the biggest impact by involving girls as the end user. Rather, the best place might be aiming your mobile component at behavior change with gatekeepers. Or sending text messages that link a girl to a service or opportunity that lives offline. It might be getting feedback on the school system or using mobile to remind parents about school meetings.

Myth 9: Mobile phones are dangerous.

Reality: Many girls and women say a mobile helps them feel safer, more independent, and more successful. The 2011 Cherie Blair/GSMA study on women and mobiles noted that 93% of women said a mobile made them feel safer and 84% felt more independent. Tech can also offer a certain level of anonymity for girls that can be beneficial in some cases. “Tech is good for girls because they can be anonymous. If you go to the bank, everyone can see you’re a girl. But if you start a business online, they don’t know that you’re a girl, so you don’t have to deal with the stereotypes,” according to Tuulia Virha, formerly of Plan Finland. Parents may also see mobiles as a tool to help them keep their children safe.

Things to consider: Mobiles can help with an increased sense of security, safety and autonomy, depending on context and situation. However, and this is what I’ll say next, mobiles also bring risk with them, and most girls we talked to for our research were aware of obvious risks – meeting strangers, exposure to pornography, pedophiles and trafficking – but not so aware of other risks like privacy. They were also not very aware of how to reduce their risk levels. So in order to really reap the safety and empowerment rewards that mobiles can bring, initiatives need to find ways to improve girls’ digital literacy and digital safety. Data security is another issue, and organizations should develop responsible data policies so that they are not contributing to putting girls at risk.

And that brings us to the other side of the coin – the myth that mobiles make girls safer.

Myth 10: Mobiles make girls safer.

Reality: Mobiles can put girls at risk. That sense of being safer with a mobile in hand can be a false one, as I noted above. Dirk Slater, from Tactical Technology Collective noted, “A big issue of working with adolescent girls is their lack of awareness of how the information they share can be stored and used. It’s important to educate girls. Look at how much information you find out about a person through social media, and what does that mean about how much information someone else can find about them.”

Things to consider: Institutions should aim to mitigate risks and help to improve girls’ digital security and safety.

Girls face safety risks on mobile at a number of levels, including:

  • Content
  • Contact
  • Data privacy and security
  • Legal and political risk (in some places they may face backlash simply for seeking out an education)
  • Financial risk (spam, hacking, spending money they don’t have on airtime)
  • Reputation risk (if they participate on social networks or speak out)

It’s also key for organizations working with girls and mobile to develop ethical policies and procedures to mitigate risks at various levels.

And that’s that for the top 10 myths! Curious to know what you think about those, and if there are other myths you find in your work with girls, mobile and learning….

 

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Starting next week, I’ll be participating in TechChange‘s course on Global Innovations for Digital Organizing: Open Data, Good Governance and Online/Offline Advocacy. I’m excited about it because the topics are among the things I’m most interested in, and I think they deserve a closer and more focused look.

I wrote a post back in November 2010 asking “where’s the ICT4D distance learning.” This led me to discover TechChange, and in January 2011 we co-hosted an “ICT4D Distance Learning Tweet Chat.” Since then I’ve been collaborating with the team to input into course ideas. I also participated as a moderator in the Mobiles in International Development course last year.

So after a year of running courses, what has TechChange learned? Nick Martin, TechChange founder, says that online learning needs to be social in order for it to be effective. “Most organizations think of ‘online learning’ as uploading powerpoints or manuals onto their website or hosting monthly webinars for their employees, but it can and should be so much more than this. By emphasizing social elements such as video chats, collaborative simulations, small group discussions and through the use of video game mechanics (point systems, progress bars, and good graphics) we keep participants engaged and connected with one another, not just the content.”

Working across time zones can be a challenge, as I also discovered when moderating the Mobiles in Development course. Scheduling in side chats was difficult, but that’s not something that’s easy to fix. TechChange tries to address this by “combining synchronous and asynchronous learning in the same platform and keeping the balance between a persistent learning network where people can socialize (via video, audio, and text) with each other and experts, and allowing people to get caught up on weekends when they fall behind so that they don’t feel left out,” according to Nick.

One thing the group learned about running this kind of course is that when engaging external experts in webinars and chats, informal-yet-direct interaction is much better than more produced content.

“We tried doing formal studio-style interviews with our experts, but found that most students just tuned out like they were watching a TV show. When the experts were just talking directly to the camera from their laptops, we found students asked more questions and participated more. They really appreciated the access to experts and weren’t particular about the production value of the webcast. Sometimes less is more,” Nick says.

Personal attention can still be a challenge, however. So TechChange emphasizes the role and importance of moderators. Their last Mobiles for International Development course had 70 students from 30 countries (see map below), making moderators a key part of personalization.

TechChange recently ran an online course for Pakistani students in partnership with IREX, where Nick says the challenge was keeping up with the students. “They brought creative ideas from their cultural exchange program with Global UGRAD-Pakistan, so we were always trying to tailor lessons around ways to improve or discuss their experiences. IREX was very focused on using our platform to create a tailored four-week program for the students, so we were able to tweak it as we went along.” (Read more here: TechChange Lessons from Training Pakistani Students Online)

The class with the Pakistani group was based on the Global Innovations for Digital Organizing course. TechChange had information ahead of time on the participant profile (the students were from Pakistan, undergraduate education, good English, decent connectivity), so they were able to maximize the experience by bringing in local partners like Pakistan Youth Alliance and Khudi and targeting youth leaders that they thought would resonate (like Prashan De Visser of Sri Lanka Unites). However, doing a class in Pakistan presented some difficulties, such as rolling power outages and load shedding. “We had to really make sure everything was optimized for low bandwidth and archiving.”

What does the future hold for TechChange? According to Nick, the group is pushing ahead on two fronts:

  1. Working with technology firms to create courses that can help them better engage their user communities
  2. Helping international development organizations integrate online learning into their local capacity building projects.

The open enrollment courses will remain, but the team will be focusing more on partnering with tech/development firms to help them build out their engaged communities. “There’s already a ton of cool tools out there that we love to teach, like Ushahidi and OpenStreetMap, but the biggest challenge isn’t tech–it’s educating and engaging communities of practice. We’re really excited about our upcoming Ushahidi course, which we developed in partnership with Ushahidi (developer Rob Baker will be the lead facilitator), but we see it as the first of many. Developers have great manuals, products, and organizations, but we can often add value by helping them educate their existing audiences and reach out to new ones.”

TechChange plans to work in the area of technical capacity building by developing more custom courses for organizations. “We see our role as changing from being the central learning location for individual students to helping development/nonprofit organizations reach out to their key stakeholders. This fulfills a key part of our mandate. It lets us provide tailor-made courses for organizations in fragile states and countries in transition.” TechChange is also looking to integrate their platform into other online learning opportunities, such as accredited courses and online conference opportunities.

It’s inspiring for me to see how quickly TechChange has built their online learning platform and how adaptable they are to the topics and themes that different people and organizations need to get a handle on in the area of ICTs and development and related humanitarian fields. I’m looking forward to participating (and speaking as a guest) in the Digital Organizing course starting on Monday!

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This is a guest post by (my boss) Tessie San Martin, CEO of Plan International USA. Tessie presented at Fail Faire DC last night. These are her thoughts on the event, and about failure in general.

I attended the most extraordinary event, hosted by the World Bank and organized and sponsored by a variety of organizations including Development Gateway, Inveneo, Jhpiego, and Facilitating Change.

The objective of the event was to share our failures using technology in a development context, and to be bold, forthright, honest, and (this is very important when talking about one’s shortcomings!) humorous. There were 10 presenters (including me).   We all agreed to be on the record.   The event, and the fact that I agreed to be on the record did make my IT and Communications teams a wee bit anxious.  But I was keen to take on this opportunity.

We do not celebrate failure often enough.  But we should.  As Tim Harford has said in his very entertaining book, Adapt, “Few company bosses would care to admit it, but the market fumbles its way to success, as successful ideas take off and unsuccessful ones die.  When we see the survivors of this process – such as…General Electric and Procter and Gamble – we shouldn’t merely see success.  We should also see the long, tangled history of failure…”

In my presentation I spoke about what I call organizational kryptonite (all the geeky readers out there like me will know that kryptonite is matter that weakens – and slowly kills with extended exposure – Superman):  being silent about your failures.  If we do not share – and learn from – failures, we will never learn what works.  If we do not take risks, and encourage experimentation, we will never advance.  The successful organizations are those that motivate risk taking. As well as transparency and openness, about what is working and what is not.

So I attended this Fail Fair, and happily shared with the audience our various challenges (a nice euphemism don’t you think?) with the application of technology for not just what I could learn (and I learned a lot) but also for what attending and presenting says about Plan.  We are failing.  And in that failure we are learning, adapting and advancing, and therefore improving our ability to improve the lives of children around the world.

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