Hedera: Reading that Fits

This image shows a postcard of the Hedera Project with the application's tagline, 'Reading That Fits'
Hedera is an online vocabulary database and readability gauge for language teaching and learning. Users can maintain a custom list of known vocabulary and analyze any text to see what percentage of words in it are known. The application helps teachers identify or create materials for their own students that meet the guidelines for readability established by research into Second Language Acquisition (SLA). Hedera also empowers learners themselves to develop their proficiency naturally through self-selected reading that is optimally readable based on the particular vocabulary that they know.

Background and Motivation

The ultimate goals of the Hedera project are: (1) to enable language teachers to implement research-based pedagogical methods, with corresponding improvements in student learning and engagement, and (2) to promote life-long language learning. Second Language Acquisition research suggests that extensive reading improves most aspects of language proficiency (including understanding of grammar, writing, and spelling, as well as reading comprehension).
The development of the Hedera project was inspired by Dr. Ivy Livingston, Preceptor in Ancient Greek and Classical Latin. Since 2017, Academic Technology for FAS has been working with Dr. Livingston to transform her idea into a robust and scalable web application for use at Harvard and beyond. Thus far, this ongoing project has benefited from generous funding provided by the Department of the Classics, the Foreign Language Advisory Group (FLAG), the Barajas Dean’s Innovation Fund for Digital Arts and Humanities, and a Targeted Support grant from the Harvard Initiative for Learning and Teaching (HILT).
The Hedera project arose out of efforts to apply Second Language Acquisition research to classical language pedagogy. Research suggests that learners need to read large quantities of material slightly above their current level of competence in order to develop fluency and learn new language items from context. However, the Latin and Greek texts that survive from antiquity simply cannot supply sufficient material that can be read by novices without frequent recourse to dictionaries or glossaries, and commentaries. Dr. Livingston’s prototype of Hedera, built using the iOS Pythonista app, was designed to help create highly readable texts for Introductory Latin students by determining whether a text contained too high a proportion of unknown vocabulary and identifying words that could be replaced or omitted to increase readability. When reading texts that had been adapted in response to the information from this app, those students showed improved reading comprehension, acquired new vocabulary through incidental encounters in the text, and demonstrated successful contextual guessing of unknown words. They also seemed more motivated to read outside of class and less intimidated by longer readings.
Originally inspired by the need to provide comprehensible readings for novice Latin learners, Hedera is being developed to incorporate additional languages, starting with Ancient Greek and Russian, in collaboration with Dr. Steven Clancy, Senior Lecturer on Slavic Languages and Literatures and Director of the Language Program in the Department of Slavic Languages & Literatures. Additional new features will include a reading environment, where the user can access their custom glossary, and making the platform adaptive by offering recommended readings as the learner’s vocabulary grows.

Technical Development

The technical development of the Hedera application has been a true story of collaboration.  The initial environment for Hedera was designed and built by developers at Archimedes Digital, whose deep familiarity with the Classical Language Toolkit and natural language processing more generally, both of which are import resources for the fundamental functionality of Hedera, have made them an ideal partner. The application has since been deployed into the Amazon Web Services (AWS) cloud, which is supported by HUIT Academic Technology. The programming language used in building Hedera is JavaScript. Concretely, the frontend is built using JavaScript's React framework and the backend using Node.js. For the database, Hedera uses MongoDB.
The technical team follows an agile methodology to develop the application, which means short iterations with frequent opportunities to demo and discuss progress between the developer, product owner, and faculty roles. Dr. Livingston’s active involvement in Hedera’s development has been a key factor in achieving milestones as well as the agreement by all team members on the definition of done.

Partnership and Development

Faculty Partner:
Ivy Livingston, Preceptor in Ancient Greek and Classical Latin
Joshua Getega, Software Engineer, Academic Technology for FAS
Artie Barrett, Software Engineer, Academic Technology for FAS
Rebecca Miller Brown, Derek Bok Center for Teaching and Learning
Sebastian Schwartz, Student Developer, Harvard College class of 2020
James Tauber, Founder-CEO-CTO, Eldarion 
Product Owner:
Bill Barthelmy, Senior Technical Architect, Academic Technology for FAS
Work on Hedera has been made possible by grant funding from the Harvard Initiative in Learning and Teaching, the Barajas Dean's Innovation Fund for Arts and Humanities, and the Foreign Language Advisory Group.