This document describes two projects aimed at improving computing students' information literacy skills. The first project encouraged use of e-journals and improved electronic searching. It resulted in students making greater use of journals and advanced search techniques, and producing better quality bibliographies. The second project developed strategies to promote evaluating information quality. It led to higher quality bibliographies citing peer-reviewed sources and quality websites. Both projects embedded activities in the curriculum and used collaboration, reinforcement, and timely contextualized learning. An iterative cognitive skills model of information literacy is presented and mapping shows how skills are developed through stages of identifying needs, locating, evaluating, solving problems, and implementing solutions.
Promoting Data Literacy at the Grassroots (ACRL 2015, Portland, OR)Adam Beauchamp
Presentation given at ACRL 2015, with Christine Murray, on teaching undergraduate students to discover and evaluate datasets for secondary data analysis.
Promoting Data Literacy at the Grassroots (ACRL 2015, Portland, OR)Adam Beauchamp
Presentation given at ACRL 2015, with Christine Murray, on teaching undergraduate students to discover and evaluate datasets for secondary data analysis.
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Blackboard’s data science team conducts large-scale analysis of the relationship between the use of our academic technologies and student impact, in order to inform product design, disseminate effective practices, and advance the base of empirical research in educational technologies.
In this presentation, John Whitmer, Director of Analytics & Research, will discuss findings from 2016. Some findings challenge our conventional knowledge, while others confirm what we believed to be true.
Archived presentation made to JISC Learning Analytics workgroup on Feb 22, 2017
Toward an automated student feedback system for text based assignments - Pete...Blackboard APAC
As the use of blended learning environments and digital technologies become integrated into the higher education sector, rich technologies such as analytics have the ability to assist teaching staff identify students at risk, learning material that is not proving effective and learning site designs that aid and facilitate improved learning. More recently consideration has been given to automated essay scoring. Such systems can be used in a formative way, such as providing feedback on initial assignment drafts or summatively through the analysis of final assignment submissions. Further, providing students with quick feedback on written assignments opens the opportunity through formative feedback to improved learning outcomes.
This presentation details a current project developing a system to analyse text-based assignments. The project is being developed for broad application, but the findings focus on an undergraduate pilot subject: ‘Ideas that Shook the World’ (a compulsory first year Bachelor of Arts subject taught on 5 campuses to more than 1000 students by 15 staff). Preliminary results of a fist scan of assignments are presented and the issues raised in developing the system presented together with an outline of additional work planned for the project. It is believed the work will have wide application where text-based assignments are utilised for assessment.
Dr Linda Corrin, University of Melbourne, discusses all things learning analytics. One of the important take-aways from this presentation is to define the question(s) before you start collecting data.
Are They Learning? Building a longitudinal model of information literacy asse...Alan Carbery
This is a paper presented at the LILAC 2016 conference in Dublin, Ireland during March 2016. This paper provides overview of a three-year assessment project in Champlain College Library - to assess the information literacy competency of students.
Presenter(s): Olga Koz.
Are you interested in working with teaching faculty to make a difference in the academic achievement of students? Would you like to move from one-shot instructions to co-designing and co-teaching courses? If so, this presentation is for you!
Learning Analytics: Seeking new insights from educational dataAndrew Deacon
CPUT Fundani TWT - 22 May 2014
Analytics is a buzzword that encompasses the analysis and visualisation of big data. Current interest results from the growing access to data and the many software tools now available to analyse this data in Higher Education, through platforms such as Learning Management Systems. This seminar provides an overview of current applications and uses of learning analytics and how it can help institutions of learning better support their learners. The illustrative examples look at institutional and social media data that together provide rich insights into institutional, teaching and learning issues. A few simple ways to perform such analytics in a context of Higher Education will be introduced.
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We draw on interviews with more than 90 students from four massive open online courses (MOOCs) to investigate how students define challenging experiences/elements within MOOCs and how they then overcome those challenges. Findings enrich nascent scholarly understanding of MOOC learner experiences, highlight dimensions of learning that are not captured by tracking logs, and provide new approaches that MOOC developers can take in improving student learning experiences.
Moving Forward on Learning Analytics - A/Professor Deborah West, Charles Darw...Blackboard APAC
Learning analytics is a 'hot topic' in education with many institutions seeking to make better use of the data available via various systems. One of the key challenges in this process is to understand the business questions that people working in various roles in institutions would like to be able to answer. However, it is also important that these questions are appropriately structured and specific in order to gather the relevant data. This session builds on the workshop run at last year's Blackboard Learning and Teaching conference where participants explored business questions and use cases for learning analytics from a range of perspectives.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
In this session, PhD students will investigate the significance of developing a research agenda and its role in professional development. Participants will explore how to craft and refine their own research agendas. Participants are invited to bring their research agendas (or statements of research interests) to share/critique.
A Systematic Analysis And Synthesis of the Empirical MOOC Literature Publishe...George Veletsianos
A deluge of empirical research became available on MOOCs in 2013-2015 and this research is available in disparate sources. This paper addresses a number of gaps in the scholarly understanding of MOOCs and presents a comprehensive picture of the literature by examining the geographic distribution, publication outlets, citations, data collection and analysis methods, and research strands of empirical research focusing on MOOCs during this time period. Results demonstrate that: more than 80% of this literature is published by individuals whose home institutions are in North America and Europe; a select few papers are widely cited while nearly half of the papers are cited zero times; and researchers have favored a quantitative if not positivist approach to the conduct of MOOC research, preferring the collection of data via surveys and automated methods. While some interpretive research was conducted on MOOCs in this time period, it was often basic and only a handful of studies were informed by methods traditionally associated with qualitative research (e.g., interviews, observations, focus groups). Analysis shows that there is limited research reported on instructor-related topics, and that even though researchers have attempted to identify and classify learners into various groupings, very little research examines the experiences of learner subpopulations.
What data from 3 million learners can tell us about effective course designJohn Whitmer, Ed.D.
Presentation of research findings and implications from a large-scale analysis of LMS activity and grade data from across 927 institutions, 70,000 courses, and 3.3 million students. This webinar will speak to the promise (and potential pitfalls) of large-scale learning analytics research to promote student success.
Blackboard’s data science team conducts large-scale analysis of the relationship between the use of our academic technologies and student impact, in order to inform product design, disseminate effective practices, and advance the base of empirical research in educational technologies.
In this presentation, John Whitmer, Director of Analytics & Research, will discuss findings from 2016. Some findings challenge our conventional knowledge, while others confirm what we believed to be true.
Archived presentation made to JISC Learning Analytics workgroup on Feb 22, 2017
Toward an automated student feedback system for text based assignments - Pete...Blackboard APAC
As the use of blended learning environments and digital technologies become integrated into the higher education sector, rich technologies such as analytics have the ability to assist teaching staff identify students at risk, learning material that is not proving effective and learning site designs that aid and facilitate improved learning. More recently consideration has been given to automated essay scoring. Such systems can be used in a formative way, such as providing feedback on initial assignment drafts or summatively through the analysis of final assignment submissions. Further, providing students with quick feedback on written assignments opens the opportunity through formative feedback to improved learning outcomes.
This presentation details a current project developing a system to analyse text-based assignments. The project is being developed for broad application, but the findings focus on an undergraduate pilot subject: ‘Ideas that Shook the World’ (a compulsory first year Bachelor of Arts subject taught on 5 campuses to more than 1000 students by 15 staff). Preliminary results of a fist scan of assignments are presented and the issues raised in developing the system presented together with an outline of additional work planned for the project. It is believed the work will have wide application where text-based assignments are utilised for assessment.
Dr Linda Corrin, University of Melbourne, discusses all things learning analytics. One of the important take-aways from this presentation is to define the question(s) before you start collecting data.
Are They Learning? Building a longitudinal model of information literacy asse...Alan Carbery
This is a paper presented at the LILAC 2016 conference in Dublin, Ireland during March 2016. This paper provides overview of a three-year assessment project in Champlain College Library - to assess the information literacy competency of students.
Presenter(s): Olga Koz.
Are you interested in working with teaching faculty to make a difference in the academic achievement of students? Would you like to move from one-shot instructions to co-designing and co-teaching courses? If so, this presentation is for you!
Learning Analytics: Seeking new insights from educational dataAndrew Deacon
CPUT Fundani TWT - 22 May 2014
Analytics is a buzzword that encompasses the analysis and visualisation of big data. Current interest results from the growing access to data and the many software tools now available to analyse this data in Higher Education, through platforms such as Learning Management Systems. This seminar provides an overview of current applications and uses of learning analytics and how it can help institutions of learning better support their learners. The illustrative examples look at institutional and social media data that together provide rich insights into institutional, teaching and learning issues. A few simple ways to perform such analytics in a context of Higher Education will be introduced.
How do learners in MOOCs attempt to resolve challenges they face?George Veletsianos
We draw on interviews with more than 90 students from four massive open online courses (MOOCs) to investigate how students define challenging experiences/elements within MOOCs and how they then overcome those challenges. Findings enrich nascent scholarly understanding of MOOC learner experiences, highlight dimensions of learning that are not captured by tracking logs, and provide new approaches that MOOC developers can take in improving student learning experiences.
Moving Forward on Learning Analytics - A/Professor Deborah West, Charles Darw...Blackboard APAC
Learning analytics is a 'hot topic' in education with many institutions seeking to make better use of the data available via various systems. One of the key challenges in this process is to understand the business questions that people working in various roles in institutions would like to be able to answer. However, it is also important that these questions are appropriately structured and specific in order to gather the relevant data. This session builds on the workshop run at last year's Blackboard Learning and Teaching conference where participants explored business questions and use cases for learning analytics from a range of perspectives.
Delivered at Innovate and Educate: Teaching and Learning Conference by Blackboard. 24 -27 August 2015 in Adelaide, Australia.
In this session, PhD students will investigate the significance of developing a research agenda and its role in professional development. Participants will explore how to craft and refine their own research agendas. Participants are invited to bring their research agendas (or statements of research interests) to share/critique.
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The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
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Role delineation in an iterative, cognitive skills based model of information literacy. Keene
1. Role delineation in an iterative,
cognitive skills based model of
Information Literacy
Judith Keene and John Colvin, University of Worcester, U.K.
Justine Sissons, Worcester College of Technology
2. Lecturer’s Optimistic View
• Problem (2004)
– In academic writing
• Inappropriate research
• Solution!!
– E-journals now available
• On-line access would suit Computing students
Therefore
• Students would use e-journals
• Research would improve
3. Reality
• Little or no improvement
• Submitted assignments suggested
– Research
• Lecture Notes
• Un-refereed www sites
• Set texts (Possibly!!)
• Little independent broader academic research
– Journals
– Other texts
4. Project 1 – using e-journals
AIMS
• Encourage use of e-journals
• Improve electronic searching skills
WHAT DID WE DO?
• Measured student skills and searching behaviour (L&T
quotient)
• Gave an e-journal induction
• Reinforced use of e-journals
• Re-measured the quotient
• Collected other information
5. Project 1 - outcomes
• Significant rise in quotient
– Making greater use of using journals
– Making more use of advanced search
techniques
• Better quality bibliographies (more journal
articles)
• Positive feedback from focus groups
6. Project 2 – better quality information
AIMS
• Encourage students to select high quality resources
• Develop strategies for promoting and embedding
evaluation skills in the L&T process
WHAT WE DID
• Measured quotient
• Tested different approaches
• Remeasured quotient
• Collected other information
7. Project 2 - outcomes
• Significant rise in quotient
• Better quality bibliographies (peer reviewed
journals and quality websites)
• Changes to delivery methods in response to
interim results and feedback
8. Common themes
• Delivery by:
– Collaboration
– Reinforcement
• Delivery
– Embedding in curriculum
– Assessment Related
– Timely
– Contextualised learning activities
11. Locate /
Retrieve
Cognitive Skills
Knowledge: (Low level)
Awareness of
Relevant journals & magazines
Library Stock
Internet Resources
Application: (Medium Level)
Able to use a variety of search engines using
Keywords
Boolean Operators
Phrase/Proximity Searches
17. Solve
Problem
Cognitive Skills
Analysis: (High Level)
Decompose problem
Evaluation: (High Level)
Information (against detailed problem needs)
Synthesis: (High Level)
Build a solution from retrieved information
Application: (Medium Level)
Apply techniques e.g.
Report structuring
Referencing
18. Teaching Computing Students
• Recent L&T Project
• Our students do not instinctively employ higher-
level cognitive skills
• Project Team recognised ‘traditional’ approach is
inappropriate
• Constructive Alignment: Biggs (2003)
• Find ‘group’ activities successful in encouraging
the use of higher-order cognitive skills
Colvin & Phelan (2006) Colvin, Price & Wright (2008)
19. How/Who: Locate / Retrieve Stage
Knowledge: (Low level)
Awareness of
Relevant journals & magazines
Library Stock, Internet Resources
Delivery
Short Joint presentation
Slides/Notes for Student use
Support
General Info Desk Enquiries
20. How/Who: Locate / Retrieve Stage
Application: (Medium Level)
Able to use a variety of search engines using
Keywords, Boolean Operators
Phrase/Proximity Searches
Delivery
Short Joint presentation
Individual Student Centred Activities
Support
1-1 Librarian Support
21. How/Who: Evaluation Stage
Analysis: (High Level)
Identifying relevant extracts
Delivery
Short Joint presentation
Student Centred Activities in Groups
Joint Consolidation
Support
1-1 Support: Lecturer or Subject
Specialist
22. How/Who: Evaluation Stage
Evaluation - Fixed Criterion: (Medium/High)
Delivery
Short Joint presentation
Student Centred Activities in Groups
Joint Consolidation
Support
1-1 Librarian Support
23. How/Who: Information Needs
Awareness: (Low Level)
Concepts associated with problem
Delivery
Routine Delivery of Course
Support
1-1 Support: Lecturer or Subject
Specialist Librarians
24. How/Who: Information Needs
Analysis: (High Level)
Analysing problem to identify
Problem aspects requiring further information
Key words
Delivery
Short Joint presentation
Student Centred Activities in Groups
Joint Consolidation
Support
1-1 Support: Lecturer or Subject
Specialist Librarian
25. How/Who: Problem Solving Stage
Analysis: (High Level)
Decompose problem
Evaluation: (High Level)
Information (against detailed
problem needs)
Synthesis: (High Level)
Build a solution from retrieved
information
Delivery
Routine Delivery of Course
Support
1-1 Support: Lecturer or Subject
Specialist Librarians
26. How/Who: Problem Solving Stage
Application: (Medium Level)
Apply techniques e.g.
Report structuring
Referencing
Delivery
Short Joint presentation
Slides/Notes for Student use
Support
1-1 Support: Lecturer or Librarian
<number>
I’m Dept Dir in ILS at UW, John is Senior Lecturer and Teaching Fellow in Computing.
This is a presentation about some project we’ve been running over the last 3 academic year to embed Inf Lit skills into the Computing Curriculum.
We’re presenting jointly because we believe collaboration has been a key factor in the success of the projects.
John will start by giving some background.
<number>
Hello
Problem
Involved with the introduction of e-j’s
Naive
<number>
<number>
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
My input ….
Non-trad – Voc “A” levels & mature/Access
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate
Context
Our abstract model of the Information Literacy
Existing Induction dealt primarily with
Locate / Retrieve
Evaluate