%0 Journal Article %1 Antoniou:2010:MVP:1841317.1841322 %A Antoniou, Angeliki %A Lepouras, George %C New York, NY, USA %D 2010 %I ACM %J J. Comput. Cult. Herit. %K hci learning mlearning mobile modeling museum profiles visitors %P 7:1--7:19 %R 10.1145/1841317.1841322 %T Modeling visitors' profiles: A study to investigate adaptation aspects for museum learning technologies %U http://doi.acm.org/10.1145/1841317.1841322 %V 3 %X The time restrictions that apply in museum learning increase the need for adaptive and/or adaptable technologies. However, deriving a visitor's profile is not an easy task, since most common ways (asking direct questions, recording user actions) are either intrusive or time consuming. Observing the visitors' movement (visiting style) within the museum could provide valuable information regarding adaptivity. In the present study, issues of visiting style were explored and statistical significance was found once different factors were analyzed. Most importantly, there seems to be a connection between the way people move in a museum and the way they prefer to approach and process information cognitively. Environmental factors that can affect the expression of visiting style were also identified.

@article{Antoniou:2010:MVP:1841317.1841322, abstract = {The time restrictions that apply in museum learning increase the need for adaptive and/or adaptable technologies. However, deriving a visitor's profile is not an easy task, since most common ways (asking direct questions, recording user actions) are either intrusive or time consuming. Observing the visitors' movement (visiting style) within the museum could provide valuable information regarding adaptivity. In the present study, issues of visiting style were explored and statistical significance was found once different factors were analyzed. Most importantly, there seems to be a connection between the way people move in a museum and the way they prefer to approach and process information cognitively. Environmental factors that can affect the expression of visiting style were also identified.}, acmid = {1841322}, added-at = {2011-02-25T10:45:36.000+0100}, address = {New York, NY, USA}, articleno = {7}, author = {Antoniou, Angeliki and Lepouras, George}, biburl = {https://www.bibsonomy.org/bibtex/27c6c79020a80669dcf8a6bd87cbd74f8/yish}, description = {Modeling visitors' profiles}, doi = {10.1145/1841317.1841322}, interhash = {399b3d34b9532f4504cbe7c70997639d}, intrahash = {7c6c79020a80669dcf8a6bd87cbd74f8}, issn = {1556-4673}, issue = {2}, journal = {J. Comput. Cult. Herit.}, keywords = {hci learning mlearning mobile modeling museum profiles visitors}, month = {October}, numpages = {19}, pages = {7:1--7:19}, publisher = {ACM}, timestamp = {2011-02-25T10:45:36.000+0100}, title = {Modeling visitors' profiles: A study to investigate adaptation aspects for museum learning technologies}, url = {http://doi.acm.org/10.1145/1841317.1841322}, volume = 3, year = 2010 }