Constructivist Analytics
Using Data to Enable Deeper Museum Experiences for More Visitors—Lessons from the Learning Sciences
Bibliographic Data
| ID | 15322749 |
|---|---|
| Authors | Matthew Berland (0000-0002-5457-1461, University of Wisconsin–Madison, corresponding author) |
| Year | 2017 |
| Volume | 20 |
| Issue | 1 |
| Pages | 3-9 |
| Publication date | 2017-01-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Visitor Studies (JOURNAL) |
| Journal identifiers | ISSN: 1064-5578 • E-ISSN: 1934-7715 |
| Publisher | Routledge (PUBLISHER • GB) |
| DOI | 10.1080/10645578.2017.1297116 |
| OpenAlex | W2609036609 |
| Language | EN |
| Citations received | 1 |
| References cited | 2 |
This article defines and outlines constructivist analytics, a framework for understanding how, where, and when the narratives we construct with advanced data analysis can affect positive social change in informal learning environments (such as museums). I ask three core questions based on this framework: How can researchers use analytics to understand what different visitors find valuable? How can we use analytics to help more visitors find value and to improve visitors' experiences when they find value? How can we present and structure analytics in ways that many different stakeholders find valuable? I then suggest possible avenues for both expanding current work in constructivist analytics and developing new angles on positive, effective, and data-rich narratives
Analytics · Construct (python library · Constructivist teaching methods · Cultural Analytics · Data science · Knowledge management · Learning analytics · Narrative · Pedagogy · Semantic analytics · Sociology · Teaching method · Value (mathematics · World Wide Web · Aesthetic Perception and Analysis · Computer Science · Data Visualization and Analytics · Online Learning and Analytics
| Citations per year | 0.17 |
|---|---|
| Citation span | 2020 - 2020 (1) |
| Highly cited | No |