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Education - Startup Digest - September 23rd - September 30th

Startup Digest


September 23, 2016

Our week's menu on tech in schools.

Starters: Artificial Intelligence, its cornerstone –big data-, and examples of AI bots.
Main course: Personalized learning.
Dessert: A pedagogical model to generate different learning strategies.

+ Your last chance to apply to be the next curator of Startup Digest Education!

Enjoy! We love you all.

Friendly reminder: If you find EDU news that is eminently share-worthy, tip us off by submitting the link here. Tweet with us @StartupDigestED.
Education Startup Digest is curated by:
Startup Digest Education

Startup Digest Education

Contact Startup Digest Education at

Aurelio Jimenez Romero

Aurelio Jimenez Romero

Contact Aurelio Jimenez Romero at

Vicky Guo

Vicky Guo - Tech investor

Contact Vicky Guo at

Deborah Chang

Deborah Chang - Educator Entrepreneur

Contact Deborah Chang at

Jessica Falkenthal

Jessica Falkenthal - Education Community + Growth Strategist

Contact Jessica Falkenthal at

How mobile commerce really works

Americans are now doing almost 33% of their online shopping on mobile devices. But what happens when you click “buy” isn’t as simple as it seems. A lot has to happen at lightning speed, with ironclad security, for mobile commerce to work. Check out this infographic, which lays out the entire process, by clicking here.

Want to support diversity in tech?

Throughout September, Betabrand will donate $5 from every Dress Pant Yoga Pants purchase to the Techstars Foundation, a nonprofit working to improve diversity in technology entrepreneurship.

Want to be the next Startup Digest Education curator? - Application due TODAY

Startup Digest Education

We are expanding our curator team to include people from more regions, specifically Asia, Latin America, and Africa. 

If you love reading education innovation news, writing, and sharing, please apply at TODAY.

We're so excited about the applications that have already come in and we also want to make sure that you don't miss your chance!

The Beginner’s Guide to Artificial Intelligence For Educators

Aj Juliani - Juliani’s blog

Artificial intelligence is already all around us. This article gives some general examples of AI and explains the basics of how it works. Brilliant. Most interestingly, it gives examples of three specific implications that could disrupt education: 

1. The death of standardized tests. 
2. A different definition of learning.
3. The emergence of AI buddies.

Do you agree?

Critical questions for big data in education

Ben Williamson - Code Acts in Education

The critical questions:

- How is ‘big data’ being conceptualized in relation to education?
- What theories  of learning underpin big data-driven educational technologies?
- Who ‘owns’ educational big data?
- Who can ‘afford’ educational big data?
- Can educational big data provide a real-time alternative to temporally discrete assessment techniques and bureaucratic policymaking?
- Is student data replacing student voice?
- Do teachers need ‘data literacy’?
- What ethical frameworks are required for educational big data analysis and data science studies?

Infographic: The bot platform ecosystem

Jon Bruner - Stephen Downes’ blog

"This infographic is only a small shard of the emerging ecosystem but it serves to highlight the developing market of AI bot platforms (Siri, Cortana, Now) along with messaging (Messenger, Allo, Skype) and the underlying AI -as-a-service (Watson, Alexa, Luis) and bot frameworks (, BotKit, Bot Framework)."

Personalized Learning in 2016: What’s Working, What’s Missing

Tom Vander Ark - Getting Smart

Since 2009, we've had the following:

Signs of Progress
1. Connectivity. Broadband connectivity and student access devices.
2. Emerging Framework.
3. School Models.
4. Platforms.
5. Tools.
6. Microcredentials. Digital form of certification that indicate when a person has demonstrated competence in a specific skill set.

1. Narrow Framework. Let's include cognitive factors and the traumatic effects of poverty.
2. Combining formative.
3. Broader aims. Include social emotional learning and productive mindsets.
4. Tradition and policy.
5. Technical difficulty.
6. Community engagement.

[Research] Learning strategies: a synthesis and conceptual model

John A C Hattie & Gregory M Donoghue - Nature

After a meta-analysis of >400 learning strategies, researchers propose the following:

- Do not separate "how to learn" and "creativity skills" from learning content.
- Define success.
- Match strategies with phases of learning. What's effective when acquiring deep learning is not necessarily effective for transferring skills.

The information is way too comprehensive to summarize fully though, so we highly recommend you dive into this information, particularly as startup founders with instructional products should use best-in-class research to guide product development.

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