Iridescent is now in its 12th year, and entering a different stage in operation. Since 2006, we have been scaling our programs worldwide. This past year, we focused our efforts on building robust, responsive systems on three fronts: 1) training and supporting partners 2) collecting and analyzing impact data and 3) sharing formative evaluation results with […]
To help you celebrate and explore these concepts, we’ve put together guides on Biomechanics and DNA. Each topic has an educator guide and a student guide. The educator guides include some facilitation tips for related design challenges, along with a quick content refresher or deeper dive into the concepts being explored. The student guide helps students understand the concepts, and guides them to build and test the prototype, with room for students to document their steps as well. The student guide also includes open-ended questions to encourage reflection.
More details about each challenge and unit below!
The last article we wrote focused on how mentoring enables personalized and deep learning (by employing a “Cognitive Apprenticeship” framework).
For this article, we will share insights gathered from high performing mentoring organizations and from the research conducted by MENTOR: The National Mentoring Partnership. Mentoring has a profound, life-changing impact on youth, especially at-risk youth as seen in the infographic from MENTOR’s “The Mentoring Effect” report:
We talked to each of the following organizations and tried to identify patterns. Each organization caters to a different target age (as seen below) and has a different approach (as we outlined in the previous article). Each is making a profound impact on the students it serves.
Some of the challenges we encountered when trying to compare such unique organizations were as follows:
Lack of time: some organizations were not able to provide cumulative data at short notice. For instance, TechBridge is a powerful program making real change in thousands of girls. Just this year they reached more than 14,000 girls, but they needed more time to pull cumulative impact data across all years.
Lack of deep data: We were only able to pull high level metrics such as increased interest in STEM, overall reach, contact hours etc. They are a step forward, but there is so much more data that we can gather to draw a more nuanced picture that will be helpful for the field.
The graphs below try to plot whatever data we were able to get and identify useful patterns.
Seeing these graphs, Mike Garringer, Director of Knowledge Management at Mentor suggested that perhaps age of operation is not the best measure of sustainability in this branch of the field, seeing that several of these programs needed the technology to be in place for their service delivery to go from idea to reality. We Teach Science is a great example of that where its Skype-like platform couldn’t have existed in a scalable way 10 years ago.
We also recognize that sheer number of contact hours has very little connection to depth of impact. It is more about the quality.
For our next article, we would love to do another round of data collection and analysis with these organizations and others that we may have unintentionally missed. Some of the variables we would like to collect are:
* data on the closeness of the mentor-mentee relationship, whether it is the primary focus of the learning experience, or the icing. We would like to connect this data to the depth of student learning gains.
* mentor retention – what aspects of the relationship inspire mentors and encourage them to come back year after year
* how much support is needed from the organization to make a good match between the mentor and mentee.
We would also love to hear any thoughts or suggestions you may have on what data points we should collect and look at.
The need is large, the field is small. There is much to be learned and improved.
(Graphic created by Audra Torres, Iridescent. Data gathered through interviews with senior leadership at organizations whenever possible. Interviews were conducted by Andrew Collins, Mentor Community Manager at Iridescent. This article is the second in a series of three).
If you do a Google search for “Role Models”, you get 5 million results. “Mentor” yields 2.6 million results, “STEM mentors” 1.6 million and “Apprenticeship” 2.6 million.
These words (and concepts) are powerful and relevant as we see a big burst of public interest. We put together a graphic in an attempt to make sense of the mentoring organizations (particularly in STEM) that we bump into frequently. We wanted to compile best practices, lessons learned, latest research stats from these organizations and tease out patterns and recommendations for the field. The graphic below is one of the lenses we used.
|Mentoring organizations that are active today.|
Most of the organizations fall within the past 30 years. Organizations such as Girls Inc., began as Girls Clubs of America in 1945, changed structure and evolved over time to respond better to the changing needs of youth.
Today there is also a rise in efforts to aggregate and share mentoring opportunities across the country, such as with the Million Women Mentors initiative and US2020. But the most prominent 20th century pioneers in the mentor landscape is Big Brothers and Big Sisters. Before 1900, mentoring was just called something different. It was called apprenticeship.
The biggest difference between apprenticeship then and now is that traditional “Michelangelo”-style apprenticeships taught skills that were visible (such as sculpting, painting, Taekwondo or any other martial art form, woodworking). The process of carrying out the task was visible both to the apprentice and master, for observation, comment, refinement, and correction. [Collins et al 1987].
Today, the apprenticeship model has evolved to teach the cognitive processes experts use to handle complex tasks. In the “cognitive apprenticeship” model experts/mentors impart both factual and conceptual knowledge in a variety of contexts, encouraging both a deeper understanding of the meaning of the concepts and facts themselves and a rich web of memorable associations between them and problem solving contexts. It is this dual focus on expert processes and situated learning that makes mentoring such a valuable solution for educational problems of “brittle skills and inert knowledge”.
A lodestar in this area has been the research by Allan Collins, John Seely Brown and Susan E. Newman (1987). They identified the following characteristics of an ideal learning environment and surprisingly – by introducing mentors – it is possible to create just such an ideal learning environment – at scale.
While most mentoring organizations share these learning environment characteristics, we have profiled at least one for each to provide an example of how this framework is being currently practiced in the field.
Domain knowledge – conceptual and factual knowledge generally found in school textbooks, class lectures, and demonstrations.
- We Teach Science – A remote tutoring and mentoring program that connects professionals with students, who tutor them in math subjects during school time
Heuristic strategies – are generally effective techniques and approaches for accomplishing tasks that might be regarded as “tricks of the trade'”.
- Intel Computer Clubhouse – leverages mentor knowledge and support to teach young people how to use modern technology and software in applicable and adaptable ways. By learning in a flexible, non-rigid environment, youth learn that there is more than one way to solve a problem.
Control strategies – As students acquire more heuristics for solving problems, they encounter a new management or control problem: how to select among the various possible problem-solving strategies, how to decide when to change strategies, and so on. For instance, a strategy for solving a complex problem might be to switch to a new part of a problem, if one is stuck on another part.
- US FIRST, ACE – STEM professionals participate on a team with students to create a novel design. This group project model provides real world experience, where mentors expose students to ‘tricks of the trade’ as well as control strategies.
Modeling, Coaching, Scaffolding and Fading – are the core of cognitive apprenticeship and help students acquire cognitive and metacognitive skills through observation and guided practice.
- iMentor, MentorNet, We Teach Science, StudentMentor.org – support one-to-one mentoring relationships. Students observe and model positive behaviors as mentors guide their practice across several years of personal coaching
Articulation and Reflection – methods designed to help students both focus their observations of expert problem solving and gain conscious access to (and control of) their own problem-solving strategies.
- The Curiosity Machine online learning platform provides children with the curriculum to do engineering projects and connects them to one-on-one mentors who give them direct feedback on how to improve their projects. Mentors support children to reflect on the process of learning and acquire metacognitive skills.
- iCouldBe – Mentees engage online in structured curricular activities to learn, explore, research and reflect on their academic and personal challenges, set goals, identify resources and put an action plan in place, supported by mentors at every stage.
Exploration – The final method (exploration) is aimed at encouraging learner autonomy, not only in carrying out expert problem solving processes, but also in defining or formulating the problems to be solved.
- Intel Computer Clubhouse – students explore new technology in a supportive learning environment. As they build skills, they are able to define their own challenges and lead their own design projects
- Technovation Challenge teaches girls how to create mobile apps to solve a problem in their community and to launch it as a business.
- Techbridge – encourages girls to brainstorm, design, and redesign projects and use technology and engineering skills in the process.
Increasing complexity – refers to the construction of a sequence of tasks and task environments or microworlds where more and more of the skills and concepts necessary for expert performance are required
- iCouldBe – Mentors guide mentees through a structured sequential online curriculum built on an architecture of Missions/Quests/Activities with increasingly challenging tasks.
Increasing diversity – refers to the construction of a sequence of tasks in which a wider and wider variety of strategies or skills are required.
- Techbridge – curriculum introduces scientific concepts and engineering design principles building girls’ content knowledge, confidence, leadership, and skills throughout the length of the year long curriculum.
- Curiosity Machine’s badge-based system allows students to gain technical skills and advance from simple to more complex engineering designs
Global before local skills – Students learn to build a conceptual map, before attending to the details of the terrain. For instance, in a tailoring apprenticeship, apprentices learn to put together a garment from precut pieces before learning to draw and cut out the pieces themselves.
- Technovation Challenge starts with girls exploring the realm of mobile app possibilities, allowing them to build a conceptual map of options before learning to actually program the app.
Situated learning – A critical element in fostering learning is to have students carry out tasks and solve problems in an environment that reflects the multiple uses to which their knowledge will be put in the future.
- Big Brothers Big Sisters – one-to-one mentoring relationship allows student to explore a variety of social and academic environments, building skills appropriate for each setting
- iCouldBe – Throughout the curriculum mentors help mentees accomplish tasks and problem-solve across academic and personal themes and apply their learning to explore future career and college goals and opportunities
Culture of expert practice – refers to the creation of a learning environment in which the participants actively communicate about and engage in the skills involved in expertise, where expertise is understood as the practice of solving problems and carrying out tasks in a domain.
- US FIRST, Technovation, Curiosity Machine– In-person robotics competition and online learning platform both support an environment in which students engage with experts in STEM fields. Mentors reinforce how math and science are used in activities outside of the classroom
Leveraging cooperation – refers to having students work together in a way that fosters cooperative problem solving. Learning through cooperative problem solving is both a powerful motivator and a powerful mechanism for extending learning resources.
- US FIRST, Technovation, ACE – teams of students and STEM professionals work together over the course of the year to create and pitch a design
- Intel Computer Clubhouse – Using the internal global social network the Clubhouse Village, members collaborate with others of diverse ages, cultures, genders, and backgrounds, and gain new perspectives for understanding the world and themselves. Global youth leadership conferences such as the Teen Summit are also held, bringing members from 20 countries together to collaborate and learn from one another.
- Techbridge – girls work with other girls and role models in cooperative brainstorming and problem solving. From icebreakers, through hands-on activities, and reflections teamwork and cooperative skills are reinforced.
Leveraging competition – refers to the strategy of giving students the same task to carry out and then comparing what each produces. One of the important effects of comparison is that it provides a focus for students’ attention and efforts for improvement by revealing the sources of strengths and weaknesses . However, for competition to be effective, comparisons must be made not between the products of student problem solving, but between the processes.
- US FIRST, Technovation – based on a challenge model, teams of students and STEM professionals compete to create and pitch a design.
The above framework is just one way to look at the exciting landscape of mentoring organizations. But it does explain why a combination of digital technology and mentors can be such a powerful solution to today’s educational problems.
Mentoring organizations today are pushing the boundaries of technology (through various forms of virtual mentoring) to maximize the mentor’s time and expertise and craft ideal learning environments.
“Perhaps less obviously, we believe that the core techniques of modelling, coaching and fading can be formalized and embedded in tomorrow’s powerful personal computers, thereby fostering a renewal of apprenticeship-style learning in our schools.”
“We believe the thrust toward computer-aided learning is an important development in education for several reasons. First, computers make it possible to give more personal attention to individual students, without which the coaching and scaffolding of apprenticeship-style learning are impossible.”
“Appropriately designed computer-based modelling, coaching, and fading systems can make cost-effective and widely available a style of learning that was previously severely limited. Of course, apprenticeship-based computer systems need not take on the total responsibility. Instead, they only need to augment the master teacher in a way that amplifies and makes her efforts more cost-effective.” [Collins et al 1987]
(Graphic created by Audra Torres. Data gathered through interviews with senior leadership at organizations whenever possible. Interviews were conducted by Andrew Collins, Mentor Community Manager at Iridescent. This article is the first in a series of three. The following articles will look more closely at the depth and type of impact each organization is having as well as organizations focused on engaging girls).
Cognitive Apprenticeship: Teaching the Craft of Reading, Writing, and Mathematics. Technical Report No. 403. By AllanCollins, BBN Laboratories, John Seely Brown, Susan E. Newman, Xerox, Palo Alto Research Center, January 1987
I watched Slumdog Millionaire many years ago and cried. I grew up in India and routinely saw little, maimed beggar children on crossroads and never thought how they got there. That movie completely shattered my protective glass.
Now I have two little girls and cannot bear to watch violence against children.
So when I heard about a group of driven young girls and mothers in Dharavi (the same slum where Slumdog Millionaire was shot), I was so energized that I could finally help right some of the hellish wrongs that we perpetrate against children.
Nawneet Ranjan, a very motivated and talented young filmmaker, approached us and told us about this group of women who were making laptop bags out of old sarees and were interested in learning about technology, so that they could make apps to market their products.
He told us a little about his own journey. His initial goal was to interview the Dharavi residents for a documentary he was making. As he started talking to the women, he was struck by their entrepreneurial spirit and their desire to improve their daughters’ future. He realized that just interviewing them for the documentary was going to be heartless, if he didn’t do something to help them as well.
That was inspiring.
And then hearing the girls talk about it in their own voices was even more inspiring.
That was last year. I shared some tablets, phones and asked Nawneet to keep in touch.
A few months later, he contacted us again and said that he had a group of 20 girls who wanted to participate in the three-month long Technovation program, and learn to create mobile apps to solve problems in their community and launch their apps on the market.
This is why this undertaking is so inspiring.
Dharavi is one of the world’s largest slums with a population greater than that of San Francisco. It is in the heart of Mumbai. Most of the girls work as house-help in people’s homes and earn $3 – a month. They go to a local government school.
They didn’t have a safe place to meet, so we helped Nawneet rent a classroom space and hook up internet, so that they could access the Technovation curriculum.
Language is a just another barrier as they are not very literate or comfortable in English.
But they have grit.
The girls’ enthusiasm to learn has inspired their mothers who have formed Mahila Mandals to help further support the girls.
The three apps that the girls are working on are to solve very real problems:
- Water access – water comes only once a day to Dharavi and only for half an hour. Children (particularly girls) have to skip school to wait hours in line. Fights are a daily occurrence. The girls are creating an app (for a cell phone) that will help families register and secure their place in the queue. The app will notify the families (via sms) when their turn is coming up, so that children dont have to waste time waiting in lines.
- Security – Rape in India is a huge problem and one that the country is struggling to address – ineffectually. The girls are creating an app that will help users press a “scream” button that will notify others — through the alarm as well as through a call made to the police.
- Health Education – Women do not have access to information — really basic information regarding personal hygiene and around more life-threatening instances, like child birth. They have no support systems or resources. The Gates blog has a great post on the state of India’s sanitation problem. The girls are working on a health education app that can provide basic health and hygiene tips to users via cell phone sms. The Mahila Mandals want to get tablets so that more women and girls can access videos and more comprehensive health education resources.
The Dharavi girls and mothers are unusual because they have the courage to seek help and the desire to fix these problems themselves. They are also unusual in that they want to befriend technology to drive this change. They want to share their stories and problems with the rest of the world – through video blogging.
We can’t wait to hear their voices and ideas.
That is the only true way to right the situation – not to look to governments, big corporations or nonprofits – but the girls. Empower the girls.
Pictures and Video by Nawneet Ranjan
Over the past few years, Iridescent has been growing and I dont have as much contact with participants as I did before. I miss that fuel.
But thankfully, every few weeks, some stories of people come through – that just make me stop and stare in amazement.
Like this one.
Senthil Kumar is an engineer at Qualcomm in Bangalore. His sister, Mani Mala, is an educator in Madurai, one of the oldest cities in the world (actually 2500 years old).
They learned about Technovation and took it upon themselves to bring Technovation to the young women of Madurai.
The logistics of this undertaking are what makes this story of grit so inspiring. It really brings perspective to first-world petty griping!
Some background on Madurai. It is famous primarily for its old, old, old, beautiful temples. People grow rubber and the city is known for its cultural traditions.
That is from a tourist’s point of view. But what about its youth? They aspire just as young people all over the world. And that is the story of Senthil. I did a quick interview with him trying to understand how he became so driven and motivated. Listen and be inspired!
Senthil and Mani Mala wanted to provide more opportunities to the young women in Madurai and recruited more than 200 women from two local universities to meet on the weekends and work through the Technovation curriculum.
They dont have internet, but that doesn’t stop them!
Senthil takes the night bus every Friday night from Bangalore (a 10 hour bus journey), reaches Madurai on Saturday morning. Teaches the girls. They work around the internet issue using an offline version of App Inventor. Senthil downloads the girl’s code on flash drives. He does the 10 hour night journey on Sunday night and goes straight to work on Monday.
He has been doing this for weeks. (The Technovation program lasts 12 weeks).
Their biggest need right now is for mentors who can help ease the load on Senthil and Mani and support the young women towards completion of their apps and business plans.
Imagine if these young women came to Silicon Valley to present their technology solutions for a better world!
Are you ready to teach your kids about the building blocks of life? Excited to begin conversations about atoms and molecules? Let’s get started creating a pH neutral drink!
|Our ingredient table|
We love teaching about science through cooking–if you missed it, check here for a discussion about the benefits of using this strategy.
- litmus paper (available online, or find instructions to make at home here)
The following are all suggestions–just choose things you have in your kitchen. Try to have a blend of some spices, sweeteners, juices, fruits and vegetables. Without a blend you won’t be able to get the drink to be pH neutral.
- spices like cloves, or cinnamon
- vegetables like beets, spinach, carrots
- sweeteners like agave nectar, honey, sugar, cocoa
- juices like apple, carrot, pomegranate
- fruits like kiwi, oranges, apples, bananas
Making Your pH Neutral Drink
Making these drinks will be a fun time for your family to test their senses of taste. Talk with your children, maybe even have them taste, the earthiness of bases (think tea, cocoa) and the sourness of acids (think lemon juice, vinegar). After this, let them know that you are trying to make the drink neutral, or with an equal taste of both acids and bases.
- Blend different types of ingredients, tasting and making changes to mixture
- Once you think you have a neutral taste, test it with the litmus paper. If it is around 7 and turns purple, it’s neutral!
- Keep trying different variations, like one without sugar, one with lots of vegetables, etc.
Science of a pH Neutral Drink
Here are some science concepts you can talk about with your families while making drinks:
- Atoms are like very small building blocks–they work together to make bigger things. There are many different types of atoms that build a diverse array of things. There are so many tastes because everything is made from different combinations of atoms.
- Atoms form together to make molecules, we can make lots of combinations
- Acids and bases are a type of molecule
- We’re trying to mix our atoms and molecules together in the drinks to make it pH neutral
- You can change the taste of a dish if it’s too bitter or sour by changing the ingredients you put in it, since each ingredient is made from different molecules. For example, if tomato juice is too sour and acidic, you can add sugar to begin making it taste more neutral.
pH Scale (note that alkaline means base or basic)