Gogia mock prospectus
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Initial plans for a dissertation on creating an assessment toolkit for the purposes of grading college and university students in networked learning settings
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Gogia mock prospectus
- 1. Laura Gogia December 2014
- 2. Period in human history in which traditional industry of the industrial revolution has been replaced by an economy based on digital information and processes. Photo: “Where is the Internet?” Flickr user Lea, https://www.flickr.com/photos/violinha/
- 3. People and information sources are linked together in a global network, allowing for unprecedented and disruptive forms of communication. Photo: “Virtual Marketing, Shirley Chan http://09820006s.blogspot.com/
- 4. Consume but also actively contribute. Affiliation Formation Creative Expression Collaborative Problem Solving Contributing to Information Circulation Photo: “Michael Wesch Keynote” by Flickr user Guilia Forsythe https://www.flickr.com/photos/gforsythe/
- 5. The new economy and culture have sparked calls for educational reform among a variety of stakeholders. 21st Century skills New Media skills Digital skills Photo: “What’s in my bag?” by Flickr user Brandy Shaul, https://www.flickr.com/photos/zoologist/
- 6. Takes advantage of: The open, distributed spaces of the web The participatory, creative nature of digital tools The power (reach) of networked communication The power (potency, innovation) of networked thinking Photo: “Network” by Simon Cockell https://www.flickr.com/photos/sjcockell/
- 7. Networked Learning emerged from informal learning environments, where formal assessments of student learning are not common and not necessarily valued.
- 8. Traditional formalized learning assessments are not consistent with networked learning pedagogies. Networked Learning Traditional Assessments Values learning as a process Values knowledge as acquired object Values collaborative work Value individual work Values remixing, synthesis Values “original” work
- 9. To create and validate an assessment toolkit for grading student performance in networked learning courses in higher education environments. Aligned Agile Valid Digital
- 10. Networked Learning Is Becoming More Popular In Higher Education. Higher Education Requires Formalized Student Assessments. Techniques Or Protocols Must Be Developed That Provide Formalized Assessment Without Compromising Pedagogical Alignment.
- 11. Networked Learning (noun): Connectivist-based learning that takes place on distributed, openly networked, & digital platforms
- 12. Connectivist-based learning that takes place on distributed, openly networked, & digital platforms Distributed: Consists of more than one platform, supporting different types of activities. Openly networked: Occurs on the open web, which allows students to interact with a larger community & provides more opportunities for students to make connections between the “spheres of learning.” Digital: Internet-based
- 13. Knowledge: a set of connections formed by actions and experience distributed across networks of human and non-human nodes. It is dynamic, changing quickly based on context. It is interpreted by the individuals who are making the connections. It rests in the diversity of opinions. Learning: the process of making decisions through the connection of information sources. (Downes, 2006)
- 14. Core skills include the ability to: ▪ Choose what to learn & interpret it based on a lens of shifting reality ▪ Nurture & maintain personal connections for continuous learning. ▪ See connections across fields, ideas, and concepts. Ability to learn through this process is more critical than current knowledge base. (Siemens, 2004)
- 15. Developing & Maintaining Personal Learning Networks Curating, Critiquing, & Organizing Data and Data Sources Connecting Concepts & People Across Spheres of Learning Sharing with Personal Learning Network Transforming Concepts into a New Product
- 16. Computer- Supported Collaborative Learning Literature (Strijbos, 2011) Participation Social Content Acquisition Individual
- 17. Participation Individual Extent to which students contribute to the social stream Transactivity Extent to which students refer to and build on each other’s contributions Transliteracy Extent to which students move across types of digital media Content Engagement Sharing Extent to which students share resources or information Construction Extent to which students use information to solve problems within the same situation in which the information was presented Transformation Extent to which students collaboratively remix or repurpose information to create new knowledge
- 18. (Fact: Digital platforms record the actions of its users and store them in ways amenable to analysis and visualization) **Preliminary Research of Social Media Analytics from a Networked Learning Course provided potential factors for student assessment.
- 19. Networked Learning Principle Assessment Principle Operationalization Blogs Twitter Establishing and Maintaining a Personal Learning Network (PLN) Participation (Individual) #Posts,Comments #Tweets Network Degree Centrality Curating, Critiquing, Organize Data and Data Sources Content Engagement (Sharing) Keywords #Links Keywords #Links Connecting or coordinating people and concepts over space, time, and spheres of learning a Participation (Transliteracy) Ratio: Posts, Comments, Tweets Participation (Transactivity) #Links Classmate Mentions #Retweets, Mentions, Replies, Links Network Betweeness Centrality Content Engagement (Construction) Keywords Links (Content) Keywords Links (Content) Transforming data into new products Content Engagement (Transformation) Content Content Sharing new product with PLN Participation (Individual) #Posts #Tweets Network Degree Centrality Participation (Transactivity) Links (Content) Classmate Mentions #Mentions, Replies, Links Network Betweeness Centrality
- 20. How can networked learning be documented for the purposes of student assessment? How can social media analytics be used to inform student assessment in networked learning environments? How does the use of social media analytics relate to a qualitative content analysis of the same data? How can social media analytics be integrated into a larger student assessment toolkit for higher education faculty?
- 21. Two Phase Research Design Toolkit Construction Toolkit Validation
- 22. Exploration of Student Data in Network Learning Environments ▪ Descriptive Statistics ▪ Quantities of student participation in the form of posts, comments, retweets, replies, mentions, etc. ▪ Social Network Analysis ▪ Characterization of interactions between students within the community ▪ Content Analysis ▪ Identification of key themes within the discourse ▪ Discourse Analysis ▪ Characterization of interactions between keywords, posts containing keywords, and students using keywords.
- 23. Secondary Data Analysis #ThoughtvectorsMOOC VCU undergraduate 2014 summer course 95 Student Participants and 30 Open Participants Students were required to blog daily and comment on each others’ posts – 98% of activity took place on WordPress Over 2309 student posts and 419 open participant posts Twitter discourse was encouraged but with limited student participation – approximately 4000 tweets total #ConnectedCoursesMOOC Digital Media Literacy Research Hub course on teaching connected courses with over 250+ active participants Weekly blogging encouraged (over 1880 posts) Active Twitter discourse among students
- 24. Application Programming Interface (API) WordPress Plug-In Microsoft Excel KBDeX Social Network Analysis Descriptive Statistics Keyword Searches NodeXL Content Analysis Discourse Analysis
- 25. Networked Learning Principle Assessment Principle Operationalized (Variables) Measurement Tool Blog Twitter Establishing and Maintaining a Personal Learning Network (PLN) Participation (Individual) Number: Posts, Comments Number: Tweets, People Followed TAGS-WP/Excel Curating, Critiquing, Organize Data and Data Sources Content Engagement (Sharing) Keywords Number: Links Keywords Number: Links KBDex TAGS-WP/Excel Product Assessment b Connecting or coordinating people and concepts over space, time, and spheres of learning a Participation (Transliteracy) Ratio: Posts, Comments, Tweets TAGS-WP/Excel Participation (Transactivity) Number: Links Classmate Mentions Number: Retweets, Mentions, Replies, Links TAGS-WP/ Excel/NodeXL Content Engagement (Construction) Keywords Content: Links Keywords Content: Links KBDex Product Assessment b Transforming data into new products Content Engagement (Transformation) Content Content KBDex Product Assessment b
- 26. Construct Validity: ▪ Qualitative Content Analysis of post and comment text ▪ How do descriptive statistics, social network analysis, and discourse analysis metrics relate to a thematic analysis of student posts and comments – with an emphasis on networked learning principles? Internal Validity: ▪ Statistical Analysis ▪ Looking for opportunities to assess internal validity through factor analyses and Chronbach alpha testing ▪ Potential correlation with post-course surveys meant to measure “connectedness” ▪ Potential correlation with final course grades
- 27. This is an exploratory process which will need continued study, replication, and refinement. Some student data obtained from courses not consistent with formal higher education settings. Results and usefulness of toolkit are impacted by instructor’s devotion to making networked learning a priority in the learning environment.
- 29. Downes, S. (2006). Learning networks and connective knowledge: Discussion paper #92. Instructional Technology Forum. Retrieved from: http://it.coe.uga.edu/itforum/paper92/paper92.html Oshima, J., Oshima, R., & Matsuzawa, Y. (2012). Knowledge building discourse explorer: A social network analysis application for knowledge building discourse. Educational Technology Research and Development, 60(5), 903–921. doi: 10.1007/s11423-012-9265-2 Siemens, G. (2004, December 12). Connectivism: A learning theory for the digital age. Retrieved from: http://www.elearnspace.org/Articles/connectivism.htm Strijbos, J.W.(2011). Assessment of (computer-supported) collaborative learning. IEEE Transactions on Learning Technologies, 4(1), 59-73.
Notes de l'éditeur
- Since the beginning of the
- The Internet (specifically Web 2.0) has created a networked culture defined by unprecedented and disruptive communication capabilities Social media facilitated by the Internet is unique, linking “the many to the many.” It allows for exponential, rapid, global spread of information; television and radio all for unidirectional broadcasting, telephones and emails allow for information exchange in relatively small circles While it is not technically ubiquitous, it is becoming increasingly more common; 80% of Internet users and 25% of worlds total population participate in social media
- In other words, they annotate, curate, combine, imitate, counter, support, criticize, and share what they consume.
- Network and Participatory have combined to change the way we understand and assess information. Networked Data Saturation Participatory Challenge to traditional hierarchies of who has the right to generate valid knowledge Cormier (2008): “The traditional method of expert translation of information to knowledge requires time – time for expertise to be brought to bear on new information, time for peer review and validation – that could make the knowledge itself outdated by the time it is verified. Information is coming too fast for our traditional methods of expert verification to adapt.” Effective members of the networked world understand that they are members of a network who play an active role in transmitting, collecting, and transforming information for the creation of knowledge
- The networked world and its participatory culture have inspired new learning theories, pedagogical frameworks, and learning formats that capitalize on the affordances of the web and aim to teach students how to capitalize on them. By affordances I mean that they take advantage of:
- Networked Learning was developed in informal learning , where assessments of student learning are not traditionally used or valued; rather, effectiveness of curriculum or instructional design are most likely to be judged by student completion, student satisfaction, or student perceptions of learning.
- The purpose of this study is to create and begin to validate an assessment toolkit for the grading of student performance in higher education networked learning courses that: Is consistent with the theoretical underpinnings of networked learning and collaborative learning assessment Takes advantage of the technological affordances of the digital platforms on which these courses take place. Provides student assessment options for higher education faculty that are easy to perform and interpret, as well as pedagogically-aligned, agile, and valid.
- There is evidence that these networked learning environments are becoming more popular in higher education settings (CCK08, CCK09, DS016, Thoughtvectors) Higher education environments require formalized student assessments, but traditional assessments are not consistent with the pedagogical stances or instructional formats of networked learning Therefore, new assessment toolkits need to be developed to aid in the assessment of student learning in networked learning environments when they are applied in formal higher education settings.
- Networked Learning (Networked Learning, Connected Learning, Distributed Learning) Occurs on distributed openly networked digital platforms Distributed: More than one platform that supports different types of activities Openly networked: occurs on the open web, which allows for interaction with a larger audience and more opportunities for students to make connections between the “spheres of learning” Digital: Internet-based
- Knowledge is a set of connections formed by actions and experience distributed across networks of human and non-human nodes. It is dynamic, changing quickly based on context, interpreted by the individuals who are making the connections. Learning is the ability to make those connections
- Note that these principles are offered in a wonky circle – they are nonlinear and iterative.
- The CSCL assessment scholars call this concept “Knowledge Creation” a combination of Knowledge Acquisition and Participation metaphors for learning. It takes into account the paradoxical tensions of social versus individual and acquisition versus participation in assessment
- Preliminary Research consisted of the literature review and an exploration of social media analytics collected from a VCU networked learning course, #Thoughtvectors, that had already taken place Social media analytics Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight. All digital platforms record the actions of its users. Learning analytics is a field of educational research that capitalizes on the “big data” collected by learning platforms to provide formative feedback for instructors and students. In the case of #Thoughtvectors, it meant looking at the available TAGS data (Twitter Analytics Google Spreadsheet) and WP (WordPress) Analytics
- Tool Kit: A collection of instruments, tools, or protocols
- is a library that includes specifications for routines, data structures, object classes and variables. The practice of publishing APIs has allowed user information to be shared from web communities to third parties for the purpose of studying or applying user data. Application Programming Interface (API) Wordpress plugins allow for the searching and copying of timestamped and url-identified content from blog posts and comments Microsoft Excel runs web queries to retrieve text or data from API Descriptive Statistics and Keyword searches NodeXL is a Microsoft Excel template that allows for easy Social Network Analysis KBDeX (Knowledge Building Discourse eXplorer) allows for the analysis of keywords in relationship with each other, posts in which they were found, and students who used them. (Oshima, Oshima, Matsuzawa, 2013).