A Smart Mobile Assessment Tool for Collecting Data in Large-Scale Educational Studies

被引:4
|
作者
Andrews, Kevin [1 ]
Zimoch, Michael [1 ]
Reichert, Manfred [1 ]
Tallon, Miles [2 ]
Frick, Ulrich [2 ]
Pryss, Ruediger [1 ]
机构
[1] Ulm Univ, Inst Databases & Informat Syst, James Franck Ring 1, D-89081 Ulm, Germany
[2] Univ Appl Sci, HSD Hsch Dopfer, Waldmarkt 3 & 9, D-50676 Cologne, Germany
关键词
Smart Mobile Assessment; Visual Literacy; Cultural Education; Large-Scale Studies;
D O I
10.1016/j.procs.2018.07.145
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Conducting scientific studies is an often frustrating and tedious task. To minimize recurring problems, such as lack of concentration or willingness to participate, and instead promote interest in the study, a smart mobile device assessment tool was developed focusing on educational studies. The tablet-based assessment tool offers a wide range of visual tasks that can be employed when conducting studies utilizing the European Framework of Visual Literacy (ENViL). Furthermore, the assessment tool is highly configurable in the field by using a centralized server and spreadsheet-based configuration files, thereby ensuring that no programming language is required to adapt the tasks on the mobile devices participating in the study. Finally, the presented framework and architecture adhere to the cross-platform and cross-device style and can be re-used and extended for any number of similar studies. (C) 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 13th International Conference on Future Networks and Communications, FNC-2018 and the 15th International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2018.
引用
收藏
页码:67 / 74
页数:8
相关论文
共 50 条
  • [21] Guest Editorial: Large-scale Data Management for Mobile Applications
    Delot, Thierry
    Geisler, Sandra
    Ilarri, Sergio
    Quix, Christoph
    DISTRIBUTED AND PARALLEL DATABASES, 2016, 34 (01) : 1 - 2
  • [22] Efficient Data Collection for Large-Scale Mobile Monitoring Applications
    Shen, Haiying
    Li, Ze
    Yu, Lei
    Qiu, Chenxi
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2014, 25 (06) : 1424 - 1436
  • [23] STEM: A software tool for large-scale proteomic data analyses
    Shinkawa, T
    Taoka, M
    Yamauchi, Y
    Ichimura, T
    Kaji, H
    Takahashi, N
    Isobe, T
    JOURNAL OF PROTEOME RESEARCH, 2005, 4 (05) : 1826 - 1831
  • [24] BIG: a large-scale data integration tool for renal physiology
    Zhao, Yue
    Yang, Chin-Rang
    Raghuram, Viswanathan
    Parulekar, Jaya
    Knepper, Mark A.
    AMERICAN JOURNAL OF PHYSIOLOGY-RENAL PHYSIOLOGY, 2016, 311 (04) : F787 - F792
  • [25] International large-scale assessment studies and educational policy-making in Chile: contexts and dimensions of influence
    Cox, Cristian
    Meckes, Lorena
    RESEARCH PAPERS IN EDUCATION, 2016, 31 (05) : 502 - 515
  • [26] The hierarchical rater model for rated test items and its application to large-scale educational assessment data
    Patz, RJ
    Junker, BW
    Johnson, MS
    Mariano, LT
    JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 2002, 27 (04) : 341 - 384
  • [27] Large-Scale Diagnostic Assessment: Mathematics performance in two educational systems
    Birenbaum, Menucha
    Nasser, Fadia
    Tatsuoka, Curtis
    EDUCATIONAL RESEARCH AND EVALUATION, 2005, 11 (05) : 487 - 507
  • [28] Valid data from large-scale proteomics studies
    Daniel Chamrad
    Helmut E Meyer
    Nature Methods, 2005, 2 : 647 - 648
  • [29] Mining large-scale smartphone data for personality studies
    Chittaranjan, Gokul
    Blom, Jan
    Gatica-Perez, Daniel
    PERSONAL AND UBIQUITOUS COMPUTING, 2013, 17 (03) : 433 - 450
  • [30] Mining large-scale smartphone data for personality studies
    Gokul Chittaranjan
    Jan Blom
    Daniel Gatica-Perez
    Personal and Ubiquitous Computing, 2013, 17 : 433 - 450