Towards Effective AI-Driven Reading Assistants: A Design Science Exploration. Hänel, M., Wambsganss, T., & Söllner, M. In ECIS 2024 Proceedings: People First: Constructing Digital Futures Together, June, 2024. Association of Information Systems in Region 2.
Paper abstract bibtex Recent advancements in AI have led to the introduction of tools that support researchers in scientific reading. Tools such as SciSpace have come to the forefront to assist users in reading scientific texts. However, there is an insufficient theoretical foundation on how to design these reading assistants as well as no evidence of their effects, especially given the recent progress. Specifically, past literature lacks insights on evaluated user requirements and design principles for the design of computer-assisted reading systems. Addressing these challenges, we draw on Design Science Research (DSR) to derive and evaluate a set of five design principles for computer-assisted reading systems. Building on flow theory as our theoretical lens, we develop and perform a first proof-of-concept evaluation of a prototypical implementation of our principles as a computer-assisted reading artifact. Our design principles support researchers and practitioners on how to design, evaluate, and compare their AI-reading tools more effectively.
@inproceedings{hanel_towards_2024,
title = {Towards {Effective} {AI}-{Driven} {Reading} {Assistants}: {A} {Design} {Science} {Exploration}},
shorttitle = {Towards {Effective} {AI}-{Driven} {Reading} {Assistants}},
url = {https://aisel.aisnet.org/ecis2024/track23_designresearch/track23_designresearch/12},
abstract = {Recent advancements in AI have led to the introduction of tools that support researchers in scientific reading. Tools such as SciSpace have come to the forefront to assist users in reading scientific texts. However, there is an insufficient theoretical foundation on how to design these reading assistants as well as no evidence of their effects, especially given the recent progress. Specifically, past literature lacks insights on evaluated user requirements and design principles for the design of computer-assisted reading systems. Addressing these challenges, we draw on Design Science Research (DSR) to derive and evaluate a set of five design principles for computer-assisted reading systems. Building on flow theory as our theoretical lens, we develop and perform a first proof-of-concept evaluation of a prototypical implementation of our principles as a computer-assisted reading artifact. Our design principles support researchers and practitioners on how to design, evaluate, and compare their AI-reading tools more effectively.},
booktitle = {{ECIS} 2024 {Proceedings}: {People} {First}: {Constructing} {Digital} {Futures} {Together}},
publisher = {Association of Information Systems in Region 2},
author = {Hänel, Martin and Wambsganss, Thiemo and Söllner, Matthias},
month = jun,
year = {2024},
}
Downloads: 0
{"_id":"9cW37JeJiRHpmDq72","bibbaseid":"hnel-wambsganss-sllner-towardseffectiveaidrivenreadingassistantsadesignscienceexploration-2024","author_short":["Hänel, M.","Wambsganss, T.","Söllner, M."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"Towards Effective AI-Driven Reading Assistants: A Design Science Exploration","shorttitle":"Towards Effective AI-Driven Reading Assistants","url":"https://aisel.aisnet.org/ecis2024/track23_designresearch/track23_designresearch/12","abstract":"Recent advancements in AI have led to the introduction of tools that support researchers in scientific reading. Tools such as SciSpace have come to the forefront to assist users in reading scientific texts. However, there is an insufficient theoretical foundation on how to design these reading assistants as well as no evidence of their effects, especially given the recent progress. Specifically, past literature lacks insights on evaluated user requirements and design principles for the design of computer-assisted reading systems. Addressing these challenges, we draw on Design Science Research (DSR) to derive and evaluate a set of five design principles for computer-assisted reading systems. Building on flow theory as our theoretical lens, we develop and perform a first proof-of-concept evaluation of a prototypical implementation of our principles as a computer-assisted reading artifact. Our design principles support researchers and practitioners on how to design, evaluate, and compare their AI-reading tools more effectively.","booktitle":"ECIS 2024 Proceedings: People First: Constructing Digital Futures Together","publisher":"Association of Information Systems in Region 2","author":[{"propositions":[],"lastnames":["Hänel"],"firstnames":["Martin"],"suffixes":[]},{"propositions":[],"lastnames":["Wambsganss"],"firstnames":["Thiemo"],"suffixes":[]},{"propositions":[],"lastnames":["Söllner"],"firstnames":["Matthias"],"suffixes":[]}],"month":"June","year":"2024","bibtex":"@inproceedings{hanel_towards_2024,\n\ttitle = {Towards {Effective} {AI}-{Driven} {Reading} {Assistants}: {A} {Design} {Science} {Exploration}},\n\tshorttitle = {Towards {Effective} {AI}-{Driven} {Reading} {Assistants}},\n\turl = {https://aisel.aisnet.org/ecis2024/track23_designresearch/track23_designresearch/12},\n\tabstract = {Recent advancements in AI have led to the introduction of tools that support researchers in scientific reading. Tools such as SciSpace have come to the forefront to assist users in reading scientific texts. However, there is an insufficient theoretical foundation on how to design these reading assistants as well as no evidence of their effects, especially given the recent progress. Specifically, past literature lacks insights on evaluated user requirements and design principles for the design of computer-assisted reading systems. Addressing these challenges, we draw on Design Science Research (DSR) to derive and evaluate a set of five design principles for computer-assisted reading systems. Building on flow theory as our theoretical lens, we develop and perform a first proof-of-concept evaluation of a prototypical implementation of our principles as a computer-assisted reading artifact. Our design principles support researchers and practitioners on how to design, evaluate, and compare their AI-reading tools more effectively.},\n\tbooktitle = {{ECIS} 2024 {Proceedings}: {People} {First}: {Constructing} {Digital} {Futures} {Together}},\n\tpublisher = {Association of Information Systems in Region 2},\n\tauthor = {Hänel, Martin and Wambsganss, Thiemo and Söllner, Matthias},\n\tmonth = jun,\n\tyear = {2024},\n}\n\n\n\n","author_short":["Hänel, M.","Wambsganss, T.","Söllner, M."],"key":"hanel_towards_2024","id":"hanel_towards_2024","bibbaseid":"hnel-wambsganss-sllner-towardseffectiveaidrivenreadingassistantsadesignscienceexploration-2024","role":"author","urls":{"Paper":"https://aisel.aisnet.org/ecis2024/track23_designresearch/track23_designresearch/12"},"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/zotero-group/schulzkx/5158478","dataSources":["JFDnASMkoQCjjGL8E"],"keywords":[],"search_terms":["towards","effective","driven","reading","assistants","design","science","exploration","hänel","wambsganss","söllner"],"title":"Towards Effective AI-Driven Reading Assistants: A Design Science Exploration","year":2024}