Exploring AppInventory, a visual catalog of applications for assisting teachers and students

  • Marco Corbatto
  • Antonina DattoloEmail author


We are witnessing a meaningful transformation of teaching and learning practices and widespread experimentation of new didactic methodologies. The availability of a huge amount of contents and learning objects on the Web is progressively transforming traditional learning design activity of teachers. However, the Web also offers another great opportunity in helping teachers adopt student centred methodologies: the availability of hundreds of Web 2.0 and mobile applications for creating and sharing digital artefacts. If incorporated into daily teaching and learning activities, they can improve the collaborative, cognitive and creative work of the students, enhancing and redefining traditional educational practices. Nevertheless, although these applications are generally easy to find and use, there is a lack of knowledge about their existence, their functions and their potential in an educational setting. In this paper we present AppInventory, a Web platform which enables teachers (and students) to visually browse through a catalog of 271 apps, semantically organized in a multi-dimensional, purpose-based taxonomy. Users can explore the catalog following personal associative paths; assign ratings, and leave comments.


Web 2.0 applications repository App 2.0 taxonomy Multimedia design and development for smart e-learning Innovative smart teaching and learning technologies Multimedia for user engagement and motivation in education Visual organizers Semantic knowledge structures 



We would like to thank all students that enthusiastically participated to this project and have contributed in different ways to the birth of this catalog. We have reported all their names on a dedicated page of the AppInventory site, hoping not to have forgotten anyone. We would like also thank Professor Alessandra Pallavicini for your support in proofreading.

This work has been partially supported by the project SMARTLAND, financed by the University of Udine (2017-19).


  1. 1.
    Anderson LW, Krathwohl DR, Airasian P, Cruikshank K, Mayer R, Pintrich P, Raths J, Wittrock M (2001) A taxonomy for learning, teaching and assessing: a revision of bloom’s taxonomy. New York. Longman Publishing. Artz, AF, & Armour-Thomas 9(2):137–175Google Scholar
  2. 2.
    Apps4edu. [Online]. Available:
  3. 3.
    Bostock M, Ogievetsky V, Heer J (2011) D3 data-driven documents. IEEE Trans Visual Comput Graph 17(12):2301–2309CrossRefGoogle Scholar
  4. 4.
    Brooke J (2013) Sus: a retrospective. J Usab Stud 8(2):29–40Google Scholar
  5. 5.
    Cherner T, Dix J, Lee C (2014) Cleaning up that mess: a framework for classifying educational apps. Contemporary Issues in Technology and Teacher Education 14(2):158–193Google Scholar
  6. 6.
    Cherner T, Lee C-Y, Fegely A, Santaniello L (2016) A detailed rubric for assessing the quality of teacher resource apps. Journal of Information Technology Education: Innovations in PracticeGoogle Scholar
  7. 7.
    Common sense education. [Online]. Available:
  8. 8.
    Corbatto M (2017) Modeling and developing a learning design system based on graphic organizers. In: Adjunct publication of the 25th conf. on user modeling, adaptation and personalization. ACM, pp 117–118Google Scholar
  9. 9.
    Corbatto M, Dattolo A (2018) Appinventory: a visual catalogue of web 2.0 and mobile applications for supporting teaching and learning activities. In: Proceedings of the 22nd international conference information visualisation - IV 2018, July 10-13, Salerno, Italy. IEEE, pp 530–535Google Scholar
  10. 10.
    Corbatto M., Dattolo A. (2018) A web application for creating and sharing visual bibliographies. In: Semantics, analytics, visualization – proceedings of SAVE-SD 2017 and SAVE-SD 2018, lecture notes in computer science, vol 10959. Springer Nature, pp 78–94Google Scholar
  11. 11.
    Costagliola G, De Lucia A, Orefice S, Polese G (2002) A classification framework to support the design of visual languages. J Vis Lang Comput 13(6):573–600CrossRefGoogle Scholar
  12. 12.
    Costagliola G, De Rosa M, Fuccella V, Perna S (2018) Visual languages: a graphical review. Inf Visual 17(4):335–350CrossRefGoogle Scholar
  13. 13.
    Dattolo A (2008) Formalizing a model to represent and visualize concept spaces in e-learning environments. In: Proceedings of international conference on web information systems and technologies - Webist 2008. Funchal, Madeira, Portugal: Insticc-INST SYST Technologies Information Control & Communication, May 4-7 2008, pp 339–346Google Scholar
  14. 14.
    Dattolo A (2009) A formal description of zz-structures. In: Proceedings of the 1st workshop on new forms of xanalogical storage and function, CEUR, no. 508, Turin, Italy, June 29, pp 7–11Google Scholar
  15. 15.
    Dattolo A, Luccio F (2009) A new concept map model for e-learning environments. Lect Notes Business Inf Process 18 LNBIP:404–417CrossRefGoogle Scholar
  16. 16.
    Dattolo A, Luccio F (2009) A state of art survey on zz-structures. In: Proceedings of the 1st workshop on new forms of xanalogical storage and function, CEUR, no. 508, Turin, Italy, June 29, pp 1–6Google Scholar
  17. 17.
    D3: Data driven documents. [Online]. Available:
  18. 18.
    Edshelf. [Online]. Available:
  19. 19.
    Educational web apps. [Online]. Available:
  20. 20.
    Essediquadro. [Online]. Available:
  21. 21.
    Isitgoonair, Mlearning class. [Online]. Available:
  22. 22.
    Free technology for teachers. [Online]. Available:
  23. 23.
    Jareño A, Morales-Morgado EM, Martínez F (2016) Design and validation of an instrument to evaluate educational apps and creation of a digital repository. In: Proceedings of the fourth international conference on technological ecosystems for enhancing multiculturality, ser. TEEM ’16. ACM, New York, pp 611–618Google Scholar
  24. 24.
    Kerren A, Kucher K, Li Y-F, Schreiber F (2017) Biovis explorer: a visual guide for biological data visualization techniques. PLoS ONE 12(11):e0187341CrossRefGoogle Scholar
  25. 25.
    Kucher K, Kerren A (2015) Text visualization techniques: taxonomy, visual survey, and community insights. In: 2015 IEEE Pacific visualization symposium (PacificVis), pp 117–121Google Scholar
  26. 26.
    Kucher K, Paradis C, Kerren A (2018) The state of the art in sentiment visualization. Comput Graph Forum 37(1):71–96CrossRefGoogle Scholar
  27. 27.
    Lee C-Y, Cherner TS (2015) A comprehensive evaluation rubric for assessing instructional apps. J Inf Technol Educ, 14Google Scholar
  28. 28.
    Li D, Mei H, Shen Y, Su S, Zhang W, Wang J, Zu M, Chen W (2018) Echarts: a declarative framework for rapid construction of web-based visualization. Vis Inf 2(2):136–146Google Scholar
  29. 29.
    Nelson TH (2004) A cosmology for a different computer universe: data model, mechanisms, virtual machine and visualization infrastructure. J Digit Inf 5:1Google Scholar
  30. 30.
    Shneiderman B (1996) The eyes have it: a task by data type taxonomy for information visualizations. In: Proceedings of the IEEE symposium on visual languages. Washington, pp 336–343Google Scholar
  31. 31.
    The european digital competence framework for citizens. [Online]. Available:

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.SASWEB Research Lab - Department of Mathematics, Computer Science and PhysicsUniversity of UdineGoriziaItaly

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