Improving eLearning through Statistical Feedback Bachelors Thesis - - PowerPoint PPT Presentation

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Improving eLearning through Statistical Feedback Bachelors Thesis - - PowerPoint PPT Presentation

Nov 14, 2022 511 likes •786 views

Improving eLearning through Statistical Feedback Bachelors Thesis Final Talk Student: Beatris Burdeva Supervisor: Prof. Dr.-Ing. Georg Carle Advisers: Marc-Oliver Pahl, Stefan Liebald Garching, 10. July 2017 Overview I. Motivation II.

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Student: Beatris Burdeva Supervisor: Prof. Dr.-Ing. Georg Carle Advisers: Marc-Oliver Pahl, Stefan Liebald Garching, 10. July 2017

Improving eLearning through Statistical Feedback

Bachelor’s Thesis – Final Talk

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I. Motivation II. Reasoning behind our Implementation Choices

  • Analysis, Initial Ideas, Related Work
  • III. Implemented Artifacts
  • Input
  • Processing
  • Visualizations
  • IV. Future Work

2

Overview

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

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  • I. Motivation

3

  • labsystem
  • eLearning platform for content creation and course management
  • ilab1 and ilab2
  • How to improve the learning process of ilab participants by making use of

the statistical data that is being gathered?

  • Additional features (feedback elements)?
  • What data?
  • What visualizations?

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

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  • II. Reasoning behind our Implementation Choices

4 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • Analysis

Best practice: Explanation: Simplicity [1] easy to understand and use focus on the content, not organization Interactivity [1, 2] collaboration different perspectives social and cooperative skills Diversity [3] diverse strategies to communicate new contents and to assess learners' progress Authenicity [1] relevant problems learning-by-doing make mistakes and learn from them Adaptivity [2, 4] good practices from traditional education Privacy [5] respective and protective of personal data

Best practices for creating a good learning process Focus - on the learners

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5

  • What is a good learning process?
  • Simplicity
  • Interactivity
  • Diversity
  • Authenticity
  • Adaptivity
  • Privacy
  • Basic set of feedback elements:
  • email
  • forum
  • chat
  • multiple choice questions/quizzes
  • free input fields/peer assessments
  • (analytical) visualizations
  • Implementation features:
  • graphical representation of

the answers (e.g. with boxes)

  • coloring of the answers
  • ...

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • II. Reasoning behind our Implementation Choices
  • Analysis (Related Work)

labsystem, Coursera, edX, Moodle

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  • II. Reasoning behind our Implementation Choices

6 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • Analysis -Related Work

Best practice: Features, contributing to fulfilling the practice:

labsystem

Coursera edX Moodle Simplicity [1]

Link each element (e.g. question) to an email body

Option to sort posts by e.g. votes Separation of posts in categories Restrict chat to a certain group of users

Interactivity [1, 2]

Comments section, visible only to tutors

Option to follow posts Option to upload files Time left until finish-deadline shown

Diversity [3]

Red/green coloring of answers

Option for learners to specify if they want to receive emails from

  • rganizations

that represent the course Check/X marks for the right/wrong answers Option to choose certainty level

Authenicity [1]

More than one attempt possible to answer a question

Explanation to the given answers (why correct/ incorrect) More than one attempt possible to answer a question Graphical representation of number of registrations per country

Adaptivity [2, 4]

Blended learning

Blended learning Blended learning Blended learning

Privacy [5]

Visibility rights

Privacy policy Privacy policy Privacy policy

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Main Findings:

  • Missing basic feedback elements in the labsystem:
  • Chat and forum
  • However: ticket system, email system
  • Visualizations by the other three platforms:
  • Coursera and edX
  • OS, browser, cookies, etc.
  • No information of how exactly they process and visualize this data.
  • Moodle – users per site, registrations per country, etc.
  • Conclusion.
  • More suitable for large scale courses.
  • No information found about visualizations relevant for us.
  • Stay with our initial ideas.

7 Beatris Burdeva (TUM) | Bachelor‘s thesis | Intermediate talk | Improving eLearning through statistical feedback

  • Related Work
  • II. Reasoning behind our Implementation Choices
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  • II. Reasoning behind our Implementation Choices

8 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • Initial Ideas

Artifact Contributes to: Audience

  • 1. Time Analysis

Simplicity, Interactivity, Diversity

  • recognition of time

related issues

  • overview of the

course workload Tutors and advisers (learners - indirect)

  • 2. Time Left

Simplicity, Interactivity, Diversity

  • increase self-refection
  • assess performance
  • better time planning

Learners

  • 3. Worst Answered

Multiple Choice (MC) and Input Questions Simplicity, Diversity

  • recognition of tasks

with worst achieved results

  • adaptation of

contents

  • emphasis on

misunderstood contents Tutors and advisers (learners - indirect)

  • 4. Additional MC

Statistics (“clicks” per anwer) Simplicity, Diversity Tutors and advisers (learners - indirect)

  • 5. Emotional Feedback -

like/dislike buttons Simplicity, Diversity, Authenticity

  • improve the emotional

engagement of the learners

  • point out preferred

contents Tutors, advisers, learners

Future work

  • D. Dimova

Implemented

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9 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • 1. Time Analysis
  • 3. Worst Answered MC and Input Questions
  • 4. Additional MC Statistics
  • existing overview page (Figure 1) - results in average, not just per team
  • comparison between terms
  • II. Reasoning behind our Implementation Choices

Figure 1: “My statistics” overview page, demo

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Learning elements in the labsystem -Analysis

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • page (p),
  • multiple choice (m),
  • input (i),
  • collection (c/C),
  • lab (l),
  • schedule (s)

Logic: p,m,i -> c -> C -> prelab/lab -> virtual page

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  • 3. Worst Answered Multiple Choice (MC) Questions

11

  • III. Implemented Artifacts

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • Visualization
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  • 3. Worst Answered Multiple Choice (MC) Questions

12

  • III. Implemented Artifacts

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • Input
  • Processing
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13 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • III. Implemented Artifacts
  • 3. Worst Answered Input Questions
  • Visualization
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14 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • III. Implemented Artifacts
  • 3. Worst Answered Input Questions
  • Input
  • Processing
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15 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • III. Implemented Artifacts
  • Input
  • Processing
  • 4. Additional MC statistics - clicks per answer
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16 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • gChartPHP [8] - PHP wrapper for the Google Chart API [10], published under the

Apache License [11]

  • III. Implemented Artifacts
  • 4. Additional MC statistics - clicks per answer
  • Visualization
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17 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • published under

GNU General Public License [12]

  • III. Implemented Artifacts
  • Visualization
  • 1. Time Analysis
  • gChartToolPHP

[9] - PHP wrapper for the Google Chart API [10],

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18 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

Already existing: Time spent per credit Figure 2: Time spent per credit [7]

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19 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • III. Implemented Artifacts
  • 1. Time Analysis
  • Input
  • Processing
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  • IV. Future Work

20 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • Implementation of the features offered by Coursera, edX and Moodle (e.g.

forum)

  • “Emotional feedback” - like/dislike buttons
  • Time Left
  • Adaptation/ complete new implementation of the existing time tracking

algorithm - advantageous

  • Implementation of features, which make the time analysis easier and more
  • precise. For example, buttons "pause", "revise" and "end"
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[1] B.H. Khan, Managing eLearning Strategies: Design, Delivery, Implementation and

  • Evaluation. Idea Group Inc., 2005.

[2] J. Hattie, Visible Learning. Routedge, 2009. [3] C.M. Reigeluth, Instructional design theories and models, Volume III. Lawrence Erlbaum Associates 1999. [4] M.V. Konstantina Chrysafiadi, “Student modeling approaches: A literature review for the last decade”, Expert Systems with Applications, 2013 [5] Official web page of the labsystem “http://labsystem.m-o-p.de/ [6] Coursera's official website - https://www.coursera.org/about/privacy [7] time tracking in the labsystem's official website: https://ilab.net.in.tum.de/timeTracking/?config=2016ws&address=l7&ttlab=7 [8] Documentation and code of the gChartPHP tool: https://github.com/pacbard/gChartPhp [9] Official web page of the gChartToolPHP wrapper tool: https://sourceforge.net/projects/gcharttoolphp/

References

21 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

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[10] Official web page of Google Charts: https://developers.google.com/chart/ [11] Apache License: http://www.apache.org/licenses/LICENSE-2.0 [12] GNU General Public License version 3.0 (GPLv3): https://sourceforge.net/directory/os:windows/license:gplv3/

References

22 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

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Thank you!

Beatris Burdeva beatris.burdeva@tum.de

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24 Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

  • III. Related Work: Coursera, edX, Moodle

Main Findings:

  • Missing basic feedback elements in the labsystem:
  • Chat and forum
  • A ticket system and emails for communicating problems instead
  • Visualizations by the other three platforms:
  • Coursera and edX – for internal use (More details in the following slides!)
  • Moodle – users per site, registrations per country, etc.
  • Conclusion.
  • More suitable for large scale courses. Stay with our own initial ideas.
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  • Gathered Non-Personal Information:
  • Visited pages of the site, order, time, “clicked” hyperlinks, IP addresses,
  • peration system and browser software used by the user, cookies and web
  • beacons. [7]
  • Purpose:
  • To track a person’s related activity on the Site, to identify repeat visitors,

time range spent on particular contents, arias of interest on the Site, etc. [7]

  • To suggest specific courses that could be of interest to the user. [7]
  • To analyze the collective behavior of the users. [7]

25

  • III. Related Work- Coursera, edX, Moodle

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback

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Figure 3: Problems with the existing time tracking algorithm

  • IV. Future Work

Beatris Burdeva (TUM) | Bachelor‘s thesis | Final talk | Improving eLearning through statistical feedback