End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making
In higher education, a wealth of data is available to advisors, recruiters, marketers, and program directors. These large datasets can be accessed using an array of data analysis tools that may lead users to assume that data sources conflict with one another. As users identify new ways of accessing...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Informatics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9709/8/3/42 |
| _version_ | 1797528908277481472 |
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| author | Amanda Briggs Francesco Cafaro |
| author_facet | Amanda Briggs Francesco Cafaro |
| author_sort | Amanda Briggs |
| collection | DOAJ |
| description | In higher education, a wealth of data is available to advisors, recruiters, marketers, and program directors. These large datasets can be accessed using an array of data analysis tools that may lead users to assume that data sources conflict with one another. As users identify new ways of accessing and analyzing these data, they deviate from existing work practices and sometimes create their own databases. This study investigated the needs of end users who are accessing these seemingly fragmented databases. Analysis of a survey completed by eighteen users and ten semi-structured interviews from five colleges and universities highlighted three recurring themes that affect work practices (access, understandability, and use), as well as a series of challenges and opportunities for the design of data gateways for higher education. We discuss a set of broadly applicable design recommendations and five design functionalities that the data gateways should support: training, collaboration, tracking, definitions and roadblocks, and time. |
| first_indexed | 2024-03-10T10:06:00Z |
| format | Article |
| id | doaj.art-e28a814ed29d403396a1fc44db45ee62 |
| institution | Directory Open Access Journal |
| issn | 2227-9709 |
| language | English |
| last_indexed | 2024-03-10T10:06:00Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Informatics |
| spelling | doaj.art-e28a814ed29d403396a1fc44db45ee622023-11-22T01:36:14ZengMDPI AGInformatics2227-97092021-06-01834210.3390/informatics8030042End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision MakingAmanda Briggs0Francesco Cafaro1Richard M. Fairbanks School of Public Health, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USASchool of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USAIn higher education, a wealth of data is available to advisors, recruiters, marketers, and program directors. These large datasets can be accessed using an array of data analysis tools that may lead users to assume that data sources conflict with one another. As users identify new ways of accessing and analyzing these data, they deviate from existing work practices and sometimes create their own databases. This study investigated the needs of end users who are accessing these seemingly fragmented databases. Analysis of a survey completed by eighteen users and ten semi-structured interviews from five colleges and universities highlighted three recurring themes that affect work practices (access, understandability, and use), as well as a series of challenges and opportunities for the design of data gateways for higher education. We discuss a set of broadly applicable design recommendations and five design functionalities that the data gateways should support: training, collaboration, tracking, definitions and roadblocks, and time.https://www.mdpi.com/2227-9709/8/3/42human-computer interactionhigher educationuser interface designlarge datasetsdata analysishuman-data interaction |
| spellingShingle | Amanda Briggs Francesco Cafaro End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making Informatics human-computer interaction higher education user interface design large datasets data analysis human-data interaction |
| title | End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making |
| title_full | End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making |
| title_fullStr | End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making |
| title_full_unstemmed | End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making |
| title_short | End-User Needs of Fragmented Databases in Higher Education Data Analysis and Decision Making |
| title_sort | end user needs of fragmented databases in higher education data analysis and decision making |
| topic | human-computer interaction higher education user interface design large datasets data analysis human-data interaction |
| url | https://www.mdpi.com/2227-9709/8/3/42 |
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