{"id":537,"date":"2020-02-24T08:08:56","date_gmt":"2020-02-24T07:08:56","guid":{"rendered":"http:\/\/ifenthaler.info\/website\/?page_id=537"},"modified":"2020-02-24T08:13:04","modified_gmt":"2020-02-24T07:13:04","slug":"educational-data-literacy","status":"publish","type":"page","link":"https:\/\/ifenthaler.info\/website\/?page_id=537","title":{"rendered":"Educational Data Literacy"},"content":{"rendered":"\n

Educational Data Literacy (EDL) is the ethically responsible collection, management, analysis, comprehension, interpretation, and application of data from educational contexts.<\/strong>
<\/p>\n\n\n\n

With the growing availability of educational data stemming from the digital learning environments and related learning and teaching processes as well as their contexts, instructional designers, e-Trainers, and teachers (among other stakeholders) gain significant information for enhancing on-demand personalised educational support of individual learners as well as reflective course (re)design for achieving more authentic training, learning and assessment experiences integrated into real work oriented tasks. However, data-driven competencies for instructional designers, e-Trainers, or teachers are not yet comprehensively addressed by existing competence frameworks and professional development programs.<\/p>\n\n\n\n

This research project on Educational Data Literacy develops and validates a framework and provides professional learning opportunities for stakeholders.<\/p>\n\n\n\n

Related project<\/h2>\n\n\n\n

Learn2Analyze<\/a>\u00a0(L2A) is an Academia-Industry Knowledge Alliance for enhancing Online Training Professionals\u2019 (Instructional Designers and e-Trainers) Competences in Educational Data Analytics, co-funded by the European Commission through the Erasmus+ Program of the European Union (Cooperation for innovation and the exchange of good practices \u2013\u00a0Knowledge Alliances<\/a>, Agreement n. 2017-2733 \/ 001-001, Project No 588067-EPP-1-2017-1-EL-EPPKA2-KA) for the period 2018-2020.<\/p>\n\n\n\n

Learn2Analyze Educational Data Literacy Competence Profile (L2A-EDL-CP)<\/h2>\n\n\n\n

The Learn2Analyze project<\/strong> has developed a comprehensive proposal for an Educational Data Literacy Competence Framework<\/strong> to enhance existing competence frameworks for instructional designers and e-trainers of online courses with new Educational Data Literacy competences.<\/p>\n\n\n\n

The Learn2Analyze Educational Data Literacy Competence Framework comprises of 6 competence dimensions and 17 competence statements, as captured below.<\/p>\n\n\n\n

L2A-EDL-CP
Dimensions<\/strong><\/p>\n\n\n\n

L2A-EDL-CP
<\/strong>Statements<\/strong><\/p>\n\n\n\n

1. Data Collection<\/strong><\/p>\n\n\n\n

1.1 Know \u2013 understand \u2013 be able to<\/strong> obtain, access and gather the appropriate data and\/or data sources<\/p>\n\n\n\n

1.2 Know \u2013 understand \u2013 be able to<\/strong> apply data limitations and quality measures (e.g., validity, reliability, biases in the data, difficulty in collection, accuracy, completeness)<\/p>\n\n\n\n

2. Data Management<\/strong><\/p>\n\n\n\n

2.1 Know \u2013 understand \u2013 be able to<\/strong> apply data processing and handling methods (i.e., methods for cleaning and changing data to make it more organized \u2013 e.g., duplication, data structuring)<\/p>\n\n\n\n

2.2 Know \u2013 understand \u2013 be able to<\/strong> apply data description (i.e., metadata)<\/p>\n\n\n\n

2.3 Know \u2013 understand \u2013 be able to<\/strong> apply data curation processes (i.e., to ensure that data is reliably retrievable for future reuse, and to determine what data is worth saving and for how long)<\/p>\n\n\n\n

2.4 Know \u2013 understand \u2013 be able to<\/strong> apply the technologies to preserve data (i.e., store, persist, maintain, backup data), e.g., storage mediums\/services, tools, mechanisms<\/p>\n\n\n\n

3. Data Analysis<\/strong><\/p>\n\n\n\n

3.1 Know \u2013 understand \u2013 be able to<\/strong> apply data analysis and modeling methods (e.g. application of descriptive statistics, exploratory data analysis, data mining).<\/p>\n\n\n\n

3.2 Know \u2013 understand \u2013 be able to<\/strong> apply data presentation methods (e.g., pictorial visualization of the data by using graphs, charts, maps and other data forms like textual or tabular representations)<\/p>\n\n\n\n

4. Data Comprehension & Interpretation<\/strong><\/p>\n\n\n\n

4.1 Know \u2013 understand \u2013 be able to<\/strong> interpret data properties (e.g., measurement error, outliers, discrepancies within data, key take-away points, data dependencies)<\/p>\n\n\n\n

4.2 Know \u2013 understand \u2013 be able to<\/strong> interpret statistics commonly used with educational data (e.g., randomness, central tendencies, mean, standard deviation, significance)<\/p>\n\n\n\n

4.3 Know \u2013 understand \u2013 be able to<\/strong> interpret insights from data analysis (e.g., explanations of patterns, identification of hypotheses, connection of multiple observations, underlying trends)<\/p>\n\n\n\n

4.4 Be able to<\/strong> elicit potential implications\/links of the data analysis insights to instruction<\/p>\n\n\n\n

5. Data Application<\/strong><\/p>\n\n\n\n

5.1 Know \u2013 understand \u2013 be able to<\/strong> use data analysis results to make decisions to revise instruction<\/p>\n\n\n\n

5.2 Be able to<\/strong> evaluate the data-driven revision of instruction<\/p>\n\n\n\n

6. Data Ethics<\/strong><\/p>\n\n\n\n

6.1 Know \u2013 understand \u2013 be able to<\/strong> use the informed consent<\/p>\n\n\n\n

6.2 Know \u2013 understand \u2013 be able to<\/strong> protect individuals\u2019 data privacy, confidentiality, integrity and security<\/p>\n\n\n\n

6.3 Know \u2013 understand \u2013 be able to<\/strong> apply authorship, ownership, data access (governance), re-negotiation and data-sharing<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Educational Data Literacy (EDL) is the ethically responsible collection, management, analysis, comprehension, interpretation, and application of data from educational contexts. With the growing availability of educational...<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":28,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-537","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=\/wp\/v2\/pages\/537","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=537"}],"version-history":[{"count":3,"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=\/wp\/v2\/pages\/537\/revisions"}],"predecessor-version":[{"id":541,"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=\/wp\/v2\/pages\/537\/revisions\/541"}],"up":[{"embeddable":true,"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=\/wp\/v2\/pages\/28"}],"wp:attachment":[{"href":"https:\/\/ifenthaler.info\/website\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=537"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}