@inproceedings{675a85ba3893494380233841babfd190,
title = "Nellodee 2.0: A quantified self reading app for tracking reading goals",
abstract = "Many readers nowadays struggle with finishing the books that they set out to read. To find a solution to this issue, we performed a design exercise which resulted in the development of a reading app that uses a quantified self (QS) approach to track reading goals, called Nellodee. This app allows readers to estimate the number of pages they would have to read to reach a daily reading goal and tracks their progress over time enabling them to reflect on their reading performance. In this paper, we present the design and implementation of our system and the results of an early pilot test are discussed.",
keywords = "Digital reading app, Goal-setting, Personal informatics, Quantified self, Reading, Reading goals, Self-monitoring, Self-tracking",
author = "Sanghyun Yoo and Jonatan Lemos and Edward Finn",
note = "Funding Information: This study was reviewed and approved by Arizona State University{\textquoteright}s Internal Review Board (STUDY00004066) and was made possible with support from the National Science Foundation (NSF #CRS0496). Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 4th International Conference on Learning and Collaboration Technologies, LCT 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017 ; Conference date: 09-07-2017 Through 14-07-2017",
year = "2017",
doi = "10.1007/978-3-319-58515-4_37",
language = "English (US)",
isbn = "9783319585147",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "488--496",
editor = "Panayiotis Zaphiris and Andri Ioannou",
booktitle = "Learning and Collaboration Technologies",
}