Browsing by Author "Gaurav, Himshwet"

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    Challenges of implementing customer discovery in learning analytics: a case study of Algole
    (University of Tartu Viljandi Culture Academy, 2014) Laks, Ivar; Gaurav, Himshwet; Sults, Marge, juhendaja; Tartu Ülikool. Viljandi Kultuuriakadeemia. Virtuaalkeskkondade loomine ja arendus
    There is a strong mismatch between demand and supply in current state of higher education in India. Over a million students aspire for a seat in the coveted top tier universities offering around 15 000 places. The students have to undergo a series of entrance examinations and based on their performance top candidates are offered a place. This gap between demand and supply has given birth to a highly competitive environment where students reach out to professional coaching institutions to improve their chances of success in the entrance examinations. The teaching methods of the coaching institutions do not consider the characteristics of different students and do not provide guidance based on the students actual needs. Algole, a learning analytics startup, is building a system to optimize students test taking strategy and help them achieve a higher score in the entrance examination. To validate the problem and solution the Algole’s team used the knowledge of Eric Ries’ Lean startup and Steve Blank’s customer development methodology. This aim of this thesis is to discover the specific challenges of implementing customer discovery methodology, the first of customer development, in the field of learning analytics. The thesis further concentrates on Algole with an aim to discover flaws in their conducted customer discovery process and provide critique and recommendations for validating their business model hypothesis. To conduct this research authors had access to all the data Algole’s team had gathered during their customer discovery process and held several interviews with the team members. Based on this information a detailed account is given about the chosen methods used by Algole and by analysing gathered data the authors of this thesis derive to the following conclusions.