Developing cloud and shared data capabilities to support primary school students in creating mobile applications that affect their communities

As technology and society become further intertwined, it is imperative that we democratize the creation of technology and educate people to be capable of harnessing the full power of computational thinking. As such, developing meaningful tools and curricula for incremental learning of computational thinking concepts starting in primary education is an important endeavor [1]. My work focuses on making Cloud technology, one of the most powerful new computer science concepts, understandable and usable by anyone without the need for extensive computer science training. I used MIT App Inventor, a blocks-based mobile application development tool for teaching computational thinking to young students, as the platform for my research. I developed CloudDB, a set of coding blocks for MIT App Inventor that allows users to store, retrieve, and share various types of data in tag-value pairs on a Redis server for their mobile applications. I created middle and high school level curricula based on CloudDB along with assessment tools to evaluate my materials and the extent to which young students can understand and utilize the concepts around shared data. Finally, I ran one of those workshops with middle school students in the MIT area. My findings indicate that teaching shared data as a core computational thinking concept is entirely feasible to students as young as middle school level. Students are capable of inferring and extrapolating other use cases and potential problems with the Cloud, such as storage limits and security concerns. When given the context of solving a problem in their lives, they are very driven and able to design and create complex independent mobile application projects using MIT App Inventor and CloudDB.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Lao, Natalie

Advisor dc:contributor.advisor

• Harold Abelson.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/113136

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/113136