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© NEXT-TELL consortium: all rights reserved

Deliverable D3.3

Methods and Specification for Activity Capturing Tools V2

Identifier: NEXT-TELL-D3.3-JRS-Activity_Capturing_Tools_V2_v08.doc

Deliverable number: D3.3

Author(s) and company: Wolfgang Halb, Roland Unterberger (JRS)

Michal Kossowski (BOC-PL)

Wilfrid Utz (BOC-AT)

Fabrizio Giorgini (EXACT)

Dean Petters, Matthew Johnson, Susan Bull (BHAM)

Internal reviewers: Vedran Hrgovcic (BOC-AT)

Wilfrid Utz (BOC-AT)

Work package / task: WP3

Document status: Final

Confidentiality: Public

Version 2012-03-30

D3.3 Methods and Specification for Activity Capturing Tools V2

© NEXT-TELL consortium: all rights reserved page ii

History

Version Date Reason of change

1 2012-01-31 document created

2 2012-02-24 Updated version (Wolfgang Halb)

3 2012-03-12 Updates on tracing and activity stepper (Wolfgang Halb, Wilfrid Utz)

4 2012-03-13 Updates on e-Portfolio, tracing, visualisations (Fabrizio Giorgini, Dean Petters, Matthew Johnson, Susan Bull, Wolfgang Halb)

5 2012-03-14 Updates on activity tracking and visualisations (Michal Kossowski, Dean Petters)

6 2012-03-16 Updates on e-Portfolio, visualisations, various (Fabrizio, Giorgini, Dean Petters, Wolfgang Halb, Roland Unterberger)

7 2012-03-28 Final version (includes updates from internal review)

8 2012-03-30 Small layout changes – version for submission

Impressum

Full project title: Next Generation Teaching, Education and Learning for Life

Grant Agreement No: 285114

Workpackage Leader: Wolfgang Halb, JRS

Project Co-ordinator: Harald Mayer, JRS

Scientific Project Leader: Peter Reimann, MTO

Acknowledgement: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 258114.

Disclaimer: This document does not represent the opinion of the European Community, and the European Community is not responsible for any use that might be made of its content.

This document contains material, which is the copyright of certain NEXT-TELL consortium parties, and may not be reproduced or copied without permission. All NEXT-TELL consortium parties have agreed to full publication of this document. The commercial use of any information contained in this document may require a license from the proprietor of that information.

Neither the NEXT-TELL consortium as a whole, nor a certain party of the NEXT-TELL consortium warrant that the information contained in this document is capable of use, nor that use of the information is free from risk, and does not accept any liability for loss or damage suffered by any person using this information.


© NEXT-TELL consortium: all rights reserved page iii

Table of Contents

1 Executive Summary .................................................................................................................................... 1

2 Introduction ................................................................................................................................................ 2

2.1 Purpose of this Document ........................................................................................................................ 2

2.2 Scope of this Document ............................................................................................................................ 2

2.3 Status of this Document ............................................................................................................................ 3

2.4 Related Documents ................................................................................................................................... 3

3 Activity Capturing Tools V2 Overview ......................................................................................................... 4

3.1 Flexible Approach...................................................................................................................................... 4

3.2 User Experience ........................................................................................................................................ 4

3.3 Integration of Information and Tools ........................................................................................................ 4

3.4 Analyses and Visualisations ...................................................................................................................... 5

3.5 System Architecture .................................................................................................................................. 5

4 Tracing Learning Applications and Activities ............................................................................................... 7

4.1 Real-time Web Browsing History .............................................................................................................. 7

4.2 Capture Web Content from Browser ........................................................................................................ 8

4.3 Capture Web Content via URI ................................................................................................................... 9

4.4 Capturing Activity in Learning Management Solutions ........................................................................... 10

4.5 Capturing Activities in Online Collaboration Tools ................................................................................. 12

4.6 Capturing Activity in Immersive Learning Environments ........................................................................ 13

4.7 Video Capture and Annotation ............................................................................................................... 13

5 NEXT-TELL Activity Stepper ....................................................................................................................... 14

5.1 User Groups and Scenarios ..................................................................................................................... 14

5.2 Mechanisms and Functionalities ............................................................................................................. 14

5.3 Architecture ............................................................................................................................................ 15 5.3.1 NEXT-TELL Metamodelling Platform ........................................................................................................................................ 16 5.3.2 NEXT-TELL Activity Stepper Execution Engine .......................................................................................................................... 17 5.3.3 NEXT-TELL Activity Stepper User Interaction and User Interface ............................................................................................. 17

6 e-Portfolio Integration .............................................................................................................................. 18

6.1 Mahara Authentication Service .............................................................................................................. 18

6.2 Import Web-Service ................................................................................................................................ 19

6.3 Future Work ............................................................................................................................................ 23

7 Visualisation of Learning Activities ........................................................................................................... 26

7.1 Moodle Chat Visualisation ...................................................................................................................... 26 7.1.1 Chat Scenario Interaction Metrics ........................................................................................................................................... 26 7.1.2 Use Case .................................................................................................................................................................................. 27 7.1.3 Available Data ......................................................................................................................................................................... 28 7.1.4 Activity Process Visualisation ................................................................................................................................................... 29

8 Conclusions ............................................................................................................................................... 31


© NEXT-TELL consortium: all rights reserved page iv

9 References ................................................................................................................................................ 32

10 Glossary .................................................................................................................................................... 33


© NEXT-TELL consortium: all rights reserved page 1

1 Executive Summary

This document provides revisions and extensions to the methods and specification for activity capturing tools from the previous version V1. The preceding methods and specification for activity capturing tools V1 have been published in NEXT-TELL deliverable D3.1. The first set of tools has been released as NEXT-TELL deliverable D3.2. For the extensions and revisions we have taken into account several sources for making adjustments. These sources include experiences from the involved NEXT-TELL partners during development and evaluation of the tools delivered, feedback received during first school trials, feedback received from the reviewers at the first review meeting and from monitoring the advances in state-of-the-art in related areas.

Updates on the focus areas for development of the second release of the NEXT-TELL toolset are given and details for revisions and extensions of the various components are discussed. The flexible approach of the entire NEXT-TELL ecosystem will be continued for the second release to enable the integration of information from various web-based tools where learning activities can occur. We will consider improvements to the user experience and also aim for a tighter integration of the various data sets. The role of an e-Portfolio as central evidence store is considered stronger. The overall system architecture remains intact and only some minor architectural changes will occur in release 2.

The capturing of learning activities are extended by the functionality to track users’ web browsing activities and the abilities of tracking activities in learning management solutions, online collaboration tools and immersive learning environments will be improved. Improvements are also made to the video capturing and annotation facility to allow a better integration in the NEXT-TELL system. The NEXT-TELL activity stepper will be upgraded and details are given in this deliverable. This document also contains a discussion of the methods and specifications for achieving a tighter integration of the e-Portfolio. Finally also the revisions and extensions related to the visualisation of learning activities are discussed.



2 Introduction

2.1 Purpose of this Document

The purpose of this document is to provide revisions and extensions to the methods and specification for activity capturing tools for V2. The preceding methods and specification for activity capturing tools V1 have been published in NEXT-TELL deliverable D3.1. The first set of tools has been released as NEXT-TELL deliverable D3.2. For the extensions and revisions we have taken into account several sources for making adjustments. These sources include experiences from the involved NEXT-TELL partners during application and evaluation of the tools delivered, feedback received during first school trials, feedback received from the reviewers at the first review meeting and from monitoring the advances in state-of-the-art in related areas.

2.2 Scope of this Document

This deliverable describes revisions and extensions to the methods and specification for activity capturing tools for V2. Therefore basic introductory information can already be found in the NEXT-TELL deliverable D3.1. The focus is on adjustments to the plans for the first tool release. The overall scope of work package 3 and hence the scope of this deliverable remains unchanged as compared to the previous deliverables (D3.1 and D3.2) of this work package.

In the overall NEXT-TELL architecture, Activity Capturing occupies a central position: it is the component that captures students' performance around learning and assessment activities as designed with the ECAAD methodology and tools (revisions and extensions to the specification of the ECAAD methodology V2 is further described in D2.3). Since the details of the Learning Environment are not to be specified by and in NEXT-TELL, but are instead specific to involved schools and teachers, the main challenge for Activity Capturing is to deal with the variety of learning tools available today to teachers and students. Even though ICT components of the learning environment are nowadays increasingly available as web-based services in the “Cloud” easing the access to these tools, this imposes new challenges to capturing data. Different, often incompatible APIs are to be considered and changes made by the providers of these web-based tools need to be taken care of. With the plethora of different online-tools available, a choice was made to support the most common tools.

Figure 1: The Overall NEXT-TELL Architecture

This report covers extensions and revisions to activity capturing, visualisation of learning activities, the integration with the e-Portfolio and video capture and annotation. This report does not provide detailed descriptions of the actual learning environment. It is also not in the scope of this deliverable to report on the underlying ECAAD layer (cf. NEXT-TELL work package 2, revisions and extensions deliverable D2.3). The Open Learner Model building on top of the activity capturing is covered in NEXT-TELL work package 4 with revisions and extensions described in deliverable D4.3.



2.3 Status of this Document

This is the final version of D3.3

2.4 Related Documents

As this deliverable describes revisions and extensions it is recommended to be familiar with the preceding work package 3 deliverables D3.1 and D3.2. In addition it also recommended consulting the strongly related revision and extension deliverables of related work packages, i.e. D2.3, D4.3, and D5.3.



3 Activity Capturing Tools V2 Overview

For the second tool release we focus on the strengths of our initial approach and adjust our priorities and plans for identified areas of improvement. The following subsections give a high-level overview of priority areas for the second release of the NEXT-TELL toolset.

3.1 Flexible Approach

As already stated in previous deliverables there exists an overwhelming amount of different learning environments/tools that are used in schools. Our flexible approach of allowing the integration of different (web-based) learning environments has in general been very welcomed. Restricting the use to a small and specific set of tools would limit the overall usefulness of the NEXT-TELL system and therefore we aim at further providing a flexible and open approach that allows the integration of different web-based tools. The decision to mainly focus on web-based tools is based on the trend that web-based tools are continuously gaining more importance and acceptance at schools. It also eases issues of local installations, software and infrastructure maintenance. In principle the access to this centrally stored data sources (where potentially relevant learning activities are recorded) is possible via the internet without having to install specific desktop software at each single client desktop. Even though these web-based tools (commonly also referred to as “cloud” tools) are centrally accessible via the internet this still poses several challenges such as the availability of suitable interfaces, the integration of different and rapidly changing interfaces, data harmonisation, user identification across different systems with different authentication mechanisms, etc. It also has to be noted that not all web-based data sources provide the same level of useful information and therefore a selection has to be made to focus on data sources that are of best value for teachers and students. A set of learning environments can already be covered by the tools developed in NEXT-TELL and further details are given in section 4.

3.2 User Experience

In order to achieve a high acceptance rate of NEXT-TELL tools in schools we aim at optimising the user experience so that also non-technical experts can make use of the tools. The second release of the NEXT-TELL toolset will improve usability issues that have been reported by users of the first toolset release. This includes easier and more intuitive access to functionality provided by NEXT-TELL tools. The heterogeneous tool environment makes this challenge quite difficult to accomplish as most other current learning tools rely on an approach where a single environment is used which allows a consistent look-and-feel with low entrance barrier. In our setting we have to integrate a set of tools provided by different partners and third parties. Providing a unified user journey along these tools is not easily achievable but by continuously gathering feedback from end users we try to identify the main usability issues and provide solutions accordingly. The role/persona model deployed will be used to give users access to the functionality most useful to them and hide technical details where appropriate.

3.3 Integration of Information and Tools

For the second toolset release we aim at achieving a tighter integration with the e-Portfolio to organise the information gathered. A central entry point will serve as the information hub for users and provide easy access to the NEXT-TELL functionality. The integration of information models across the various tools will also be intensified in the second release. This includes harmonisation of role models with associated access rights and a smooth information flow from backend data sources. The common information model will expand from the central user management that has been realised with the Central Authentication Service and include additional metadata that is shareable among the NEXT-TELL tools by taking privacy and security concerns into consideration (see D2.10). The stronger integration planned for the second toolset releases will also contribute to an improved user experience.



3.4 Analyses and Visualisations

The second release toolset will provide additional analysis-modules and visualisations of learning activities which are covered in section 7 of this deliverable. These additional features have been developed in close cooperation with participating schools to meet their needs.

3.5 System Architecture

The overall system architecture remains unchanged. We have made some minor revisions and extensions related to the technical implementation of individual component integrations. Based on feedback from the first

review we will explore and strengthen the role of an e-Portfolio as data store for evidence produced by students. We also take suggestions into account for making the access to more relevant information easier.

This has only minor impact on the overall system architecture as the main data flow remains almost unchanged. The individual details are covered in more depth in the following sections.

Figure 2 provides a simplified overview of the conceptual architecture. Some details have been omitted to ease the comprehension of the architecture. Mainly components related to activity capturing are discussed here. The teacher inquiry and strategic layer are not discussed here (cf. NEXT-TELL deliverables from work package 5). The full details of the conceptual architecture have already been presented in NEXT-TELL deliverable D3.1. The NEXT-TELL Portal provides easy access to all relevant components. Based on user roles and personal profiles the relevant options are displayed in the portal. From the portal it is possible to access the modelling tools for creating ECAAD and activity models (cf. NEXT-TELL deliverable D2.3). The activity models serve as a base for the activity stepper (cf. section 5). The activity stepper is integrated with the different learning environments and students can execute their activity in the respective learning environment where information/evidence is captured from (cf. section 4). Evidence is stored to a large extent in the e-Portfolio (cf. section 6). This evidence is analysed and activity visualisations as well as the open learner model are created (cf. section 7 and NEXT-TELL deliverable D4.3). For a detailed discussion of the architecture and all dependencies and data flows deliverable D3.1 serves as a reference.

Figure 2: Simplified NEXT-TELL Conceptual Architecture Overview



From an end-user point of view we also plan to evaluate the possibility of upgrading the NEXT-TELL portal for release 2 to a personalized learning environment that provides an enhanced user experience and more flexibility. The integration is planned along the widget specification from W3C which has finally matured and received W3C Recommendation status on 27 September 2011 [W3C, 2011]. An initial feasibility study showed that this strategy could potentially be a viable evolutionary step of the NEXT-TELL eco-system. The technical realisation of the portal could be achieved with a new mash up engine called Apache Rave [Apache, 2011] that is currently in incubator status at the Apache Software Foundation. This means that the software is still in an experimental state and constantly evolving. We will have to follow the development progress of this third-party technology, evaluate the reliability of this component and assess potential uses of this technology in NEXT-TELL. By following the standardized widget approach we gain stronger interoperability of the components developed in NEXT-TELL. This allows for two-fold integration strategies of NEXT-TELL and third-party components as depicted in Figure 3.

Figure 3: Integration scenarios based on standardized interfaces

By implementing some interfaces of NEXT-TELL applications as widgets adhering to the W3C widget specification we can integrate those widgets in a new NEXT-TELL portal based on mash up technology and also make some of these widgets available to the wider public for easy integration in other portals. These widgets could also be used as a base for stand-alone widgets in desktop widget containers (like e.g. Apple Dashboard, Windows Sidebar, Google Desktop, etc.) or for mobile widgets to be used in mobile phones and tablets. Users of the NEXT-TELL Portal gain more flexibility and can also embed other third-party content (e.g. translator widget, Twitter, Wikipedia, YouTube, etc.) provided via widgets in their personal learning environment. However, we still have to assess the maturity of these technologies and plan to have a “lite” version of the new technology stack in NEXT-TELL release 2.

NEXT-TELL Portal

NEXT-TELL Apps

Third-party content

Other Portal



4 Tracing Learning Applications and Activities

For the second release of the NEXT-TELL toolset some improved functionality will be provided. The most notable new feature to be deployed is the ability to trace all web browsing activities of a user, which is completely under the control of the user. Several improvements will also be available for other components along with enhanced integration. As has already been described in NEXT-TELL deliverable 3.2 we have postponed low-level data capturing of internet activity based on an SSL-encrypted proxy software solution such as SSL-Explorer. The collection of a real-time web browsing history will replace this initial proxy-based solution

4.1 Real-time Web Browsing History

In order to capture the Web activities of a student we have started the development of a real-time web browsing history tool. This tool allows to gather information on webpages (URIs) visited during a session and also captures search terms used. To maximize user acceptance and respect the user’s privacy, data will only be captured when the user/student expressly confirms to have his data captured. Visual user interface elements will also inform the user whenever data is being captured. No hidden data capturing takes place.

The real-time web browsing history currently under development for release 2 is based on an add-on for the Firefox browser. The overall interaction pattern is depicted in Figure 4. Upon activation by the user (clicking the “REC” button) the browser add-on will collect information on the URIs visited. On the client-side a special filter software technology will be integrated to delete any sensitive data before sending it to the NEXT-TELL web browsing logging server to maximize security and minimize the risk of misusing the collected data. Cleaned information about the pages visited will be securely transmitted to a NEXT-TELL server and is available for later analysis. Data will also be stored securely with tight access control monitoring.

Figure 4: NEXT-TELL Real-time Web Browsing History Overview

Currently the development of this web-browsing tracing feature has been started as add-on for Firefox due to several reasons: Some statistics state that Firefox is still the most widely used browser in February 2012 (e.g. according to [W3Schools, 2012] 36.6% Firefox, 36.3% Chrome and 19.5% Internet Explorer users in February 2012.) According to statistics from StatCounter as presented in Figure 5 the Firefox browser is the second most-often used browser worldwide. In addition, the existing developer team in NEXT-TELL already has experience in developing Firefox add-ons, which increases the development speed. For these reasons we started with the development of an add-on for Firefox. However, given the current statistics we will consider also porting the web browsing tracing feature to Internet Explorer and Google’s Chrome. Chrome has seen a rapid increase in

User side

Browser

Input raw browsing

data

Clean data

Clean browsing data NEXT -TELL Web

Traces store

NEXT-TELL Web Analysis



user figures and therefore we will also consider targeting this browser. When add-ons for these three browsers (Firefox, Chrome, Internet Explorer) are available, we will be able to reach around 90% of browser market share.

Figure 5: Usage share of web browsers, Source: [Wikimedia, 2012]

The decision for capturing web browsing history data was taken following the initial idea of using a proxy based solution. However, several reasons ranging from usability to privacy issues have been discovered in this initial proxy-based approach. Similar difficulties were experienced when evaluating further solutions ranging from network infrastructure-based approaches to client-side monitoring tools based on strong integration in the client’s operating system. All the previously considered approaches would either require substantial deployment or development efforts that are not realisable within NEXT-TELL. With the current solution based on a browser add-on, the user gets the overall control and can decide if the browsing data should be captured or not. The captured browsing data can then be used for further useful analyses that will be fully deployed in NEXT-TELL’s final release. However, initial analysis features will also be ready for R2 of the NEXT-TELL toolset. With this approach we can capture the pages visited and also the search terms used in popular search engines to find information. This data could be used to analyse which web information was most useful for students, which web resources have been discovered by the same group of students, etc.

However, there are still web interactions that cannot be captured by this approach. Therefore we also plan to develop two further tracing tools as outlined in the subsequent sections.

4.2 Capture Web Content from Browser

The feature present above to capture real-time web browsing history is only designed to capture URIs visited which also includes search terms used in popular search engines. However, with the web content capturing presented in this subsection it will also be possible to capture actual “evidence” produced by students in a web-based application. Simply using an URI is not sufficient to capture the evidence created by a user. Access restrictions and dynamically created content based on form feedback make it impossible to retrieve the produced content easily afterwards. Flash based questionnaires and games make it even more difficult to capture the actual evidence produced by the student. A possible solution to allow the student to capture any data that he produced online is to allow web snapshots to be submitted as evidence to the NEXT-TELL activity evidence repository. In the web browsing tracing add-on an additional feature will be implemented that allows to easily submit to the evidence store the content that is visible in the user’s browser. For R2 this will be included in the add-on for Firefox. This approach allows to submit almost every web-based content to the NEXT-TELL evidence repository and works for all applications, even if they are not natively integrated with NEXT-TELL. In comparison to natively integrated NEXT-TELL components this approach only allows to capture the outcome of an activity without background metadata about the creation of this piece of evidence. To give an example for differences between the different approaches consider a document created on Google Docs. With the “Capture Web Content from Browser” approach it is possible to capture the actual produced output. On the other hand, through the full/native integration of GDocs in NEXT-TELL it is not only possible to capture the actual output but also information about how this document was created, e.g. which user contributed,



revision history, etc. In comparison the full/native integration requires additional development effort to access each individual API. With the “Capture Web Content from Browser” approach it is possible to capture the entire Web – no matter where the content has been produced on the Web.

4.3 Capture Web Content via URI

For cases where student created evidence can be retrieved on the web via an URI we will also make a tool available that can be used in Internet Explorer and Chrome in NEXT-TELL R2 already. With this tool based on bookmark technology it will be possible to submit produced evidence to the NEXT-TELL evidence repository.

Figure 6: Example of Web content capture via URI in Internet Explorer

Figure 6 provides an example of how the “web content capture via URI” feature will look like in Internet Explorer. By simply pressing a button in the bookmark/favourites toolbar the current webpage URI will be submitted to the NEXT-TELL evidence repository. The student can use this feature to document learning evidence that he has created outside of natively integrated NEXT-TELL tools.

The intention for also offering this approach is to have an easy-to-use tool that is available in different browsers. A comparison of the different web content capturing approaches is given below:

Full/native integration of tools

Real-time Web Browsing History

Capture Web Content From Browser

Capture Web Content via URI

Main purpose Tight integration with tools

Capture web browsing history

Submit evidence from any web page

Submit link to web page with evidence

Target tools Moodle, SecondLife, EVA, GDocs, RepGrid, etc.

The Web The Web The Web

Data captured All data available through API

URIs visited, search terms used

Content as displayed in browser

URI

Browser restrictions in NEXT-TELL R2

None, all web clients (desktop/mobile)

Firefox

(Internet Explorer, Chrome planned)

Firefox

(Internet Explorer, Chrome planned)

Firefox

Internet Explorer

Chrome

Even though there is a choice of different technologies and approaches to capturing web interactions we target an easy-to-use ecosystem. The user will be presented with the right tool to capture his learning evidence based



on the planned activity and the target systems used for the learning activity. To improve the user experience we will also investigate different user interaction designer best practices to make the use of the NEXT-TELL tool stack as easy as possible.

4.4 Capturing Activity in Learning Management Solutions

In D3.2 we started to analyse which, among the vast amount of information available in the Learning Management Solution Moodle, can be considered of value for the analysis of students’ behaviour. Logs data like attended online courses, the time spent on an activity, results of quizzes etc. were thought important for that analysis. In order to export the log data outside Moodle, a new web-service have been developed.

However, from some discussions with NEXT-TELL teachers is emerged the supportive role of the use of the Moodle chat in learning English as a second language.

From that the need to implement a web-service which allows the extraction of the chat’s content data and the migration of this information to the OLM for the visualisation of some interaction metrics useful to the teacher for the assessment (see section 7.1).

The rest of the section describes the implemented web services to get the list of the Moodle chat and retrieve the related contents. The web services don’t provide any processing on data returned like the words counting, number of chat entries, distribution of number of words used per entry etc.

Get all chats for the course

There are two ways to retrieve the list of chats of a course: using the course id or the name of the course.

Get course’s chats using course id

Example for all chats of the course “eP Introduction” which id = 2:

http://research01.exact-learning.com/Moodle_nt/wspp/service_pp2.php?wsusername={user}&wspassword={pass}&wsformatout=dump&wsfunction=get_instances_bytype&courseids=2&type=chat&idfield=id

Get course’s chats using shortname

Example for all chats of the course with shortname=eP+Introduction:

http://research01.exact-learning.com/Moodle_nt/wspp/service_pp2.php?wsusername={user}&wspassword={pass}&wsformatout=dump&wsfunction=get_instances_bytype&courseids=eP+Introduction&type=chat&idfield=shortname

IMPORTANT: the shortname is case sensitive.



The call returns data structure like the following:

Get chat posts

It’s used to retrieve the posts of a chat according the specified filtering mechanism.

Query format:

wsfunction=get_chat_posts&chatid=1&userids=[id1,id2]&groupids=[id1,id2]&fromdate=[..]&todate=[..]

Where:

chatid = id (mandatory)

userids = id1,id2 (0 or more)

groupids = id1,id2 (0 or more)

fromdate = <timestamp> (optional)

todate = <timestamp> (optional)

Get all posts of a chat

Example for Chat id = 7

http://research01.exact-learning.com/Moodle_nt/wspp/service_pp2.php?wsusername={user}&wspassword={pass}&wsformatout=dump&wsfunction=get_chat_posts&chatid=7&groupids=&userids=&fromdate=&todate=

Get posts of a chat filtered by user(s)

Example for Chat id = 7, Users = 6 and 2

Array

(

[0] => stdClass Object

(

[id] => 7

[course] => 2

[name] => eP introduction

[coursemodule] => 145

[module] => 2

[section] => 1

[visible] => 1

[groupmode] => 1

[groupingid] => 0

[groupmembersonly] => 0

[url] => http://research01.exact-learning.com/Moodle_nt/mod/chat/view.php?id=145

[type] => chat

[timemodified_ut] => Thursday, 1 January 1970, 01:00 AM

[summary] =>

)

)



http://research01.exact-learning.com/Moodle_nt/wspp/service_pp2.php?wsusername={user}&wspassword={pass}&wsformatout=dump&wsfunction=get_chat_posts&chatid=7&groupids=&userids=6,2&fromdate=&todate=

The call returns data structure like the following:

4.5 Capturing Activities in Online Collaboration Tools

For capturing activities in online collaboration tools such as Google Docs we have already presented some implemented solutions in NEXT-TELL deliverable D3.2. In addition to the presented implementations we will extend the GDocs Progress Tracker for R2 with some additional features. Based on comments made in a document we will extract the comments and visualize the discussion around a document also in an overview. The underlying data can already be extracted by accessing the GData API and is already made available for further analysis.

However, for accessing documents stored in GDocs there exist several approaches based on the access settings. From a technical point of view the easiest way of accessing a document is if the document is made publicly available. The downside of this approach is that it is not desirable in many cases to have the documents accessible by everyone without access restrictions. Another option is to make the document private (which is the default setting for all documents created in GDocs) and share it where necessary. The sharing of a private document can be done on individual account basis, e.g. the student privately shares his document with the teacher. The downside of this approach is that it actively requires the student to share each document reducing the ease-of-use. Another approach is to organize documents in a collection that is shared with a specific class/group. In that way the sharing settings only need to be made once. The downside here is that

Array

(


(

[id] => 1578

[chatid] => 7

[userid] => 6

[groupid] => 0

[system] => 1

[message] => enter

[timestamp] => 1327657550

)


(

[id] => 1580

[chatid] => 7

[userid] => 6

[groupid] => 0

[system] => 0

[message] => this is a test

[timestamp] => 1327658797

)

...



usually all members of the group can also access documents by peer students which is also not desirable in every case, but it already provides much more privacy and ease-of-use than the approaches presented above. In the first version of the GDocs Progress Tracker we have implemented the functionality to analyse all documents that are accessible for a teacher. This includes individually shared and collection-shared documents.

The most flexible approach relies on having a Google Apps for Education domain registered for the school. In that case different accounts with fine-grained access controls can be established. For instance it can then be configured to have teacher accounts that can access all documents created by students and also control whether or not students should be able to view or edit peer students’ documents. This requires however that each school register for a free-of-charge Google Apps for Education domain. We will consider this approach also for further developments and some of our partner schools already use such an account.

4.6 Capturing Activity in Immersive Learning Environments

As already outlined in the preceding NEXT-TELL deliverables D3.1 and D3.2 we also support immersive learning environments such as Second Life and Open Simulator in NEXT-TELL. Several scenarios have been developed and sessions with students have also been conducted in the course of the project. We have already improved the data capturing facilities and plan on improving the integration of generated tracking data from these virtual worlds. For release 2 we will integrate the existing data captures more with the overall NEXT-TELL system and also improve the usability of the tools based on feedback we received from the on-going school studies where details can be found in deliverable D6.3.

4.7 Video Capture and Annotation

With the EVA tool described in the preceding WP3 deliverables we have already deployed a tool that supports the annotation of captured video. For release 2 of the NEXT-TELL toolset we plan to make some usability improvements and make the integration with video capturing easier. This applies in particular to capturing interactions from SecondLife. A stronger integration with the e-Portfolio will also be implemented for release 2. External tools for video capturing and annotation will also be considered in the second release of tools in concordance with the priority areas expressed in section 3 of this deliverable.



5 NEXT-TELL Activity Stepper

The NEXT-TELL Activity Stepper represents the human-based operationalization of models developed within the ECAAD environment, especially focusing on learning activity designs, incorporating assessment triggers. As such, the NEXT-TELL Activity Stepper interprets the released models from the central model repository and provides the user with a wizard-like step-through possibility. Information such as description and support texts, the graphical representation, related learning services (defined here in a broad sense ranging from learning objects/material to interactive components/application) as modelled using ECAAD are presented to the user to be used to solve/accomplish the learning tasks.

5.1 User Groups and Scenarios

2 scenarios are envisioned for the NEXT-TELL Activity Stepper relating to the respective user group:

Model Validation and Walkthrough: in order to assess the design and its effectiveness/appropriateness, the designer has the possibility to assess and test-run the design. This scenario is also important from a knowledge sharing perspective, to view and assess other participants’ designs and evaluate possible patterns that can be reused.

Model Animation and Operation: the learner uses the activity stepper to animate and operationalize the learning activity model handed over from the ECAAD planner. The main functionality relate to the learner itself to provide an environment that makes the complexity of a distributed system transparent to them. The user experience in the activity stepper aims at providing different functionality of different components of the NEXT-TELL environment within one single user interface. A scenario for such an integration relates to the collection of evidence using the NEXT-TELL Mahara environment: the Activity stepper should allow to enter evidence information in any format that Mahara supports to provide evidence, that the student has accomplished the task as defined during the planning phase.

Progress Analysis: the teacher assesses from a quantitative (time, interaction count) as well as qualitative perspective the progress within a learning activities sequence. In addition feedback is provided to the individual learner if needed.

5.2 Mechanisms and Functionalities

The functionality of the activity stepper is derived from mock-up demonstration and analysis with end-users partners/experts within the project consortium presented in the following:

Hand-Over/Release Mechanism: a release mechanism is envisioned to support the hand-over from the planner into the execution environment. The release mechanism provides the following functionality:

o Validation/Verification: a validation is needed to make sure that the model designed in the modeller is executable. Graph-theory based algorithms can be used to validate that all nodes defined are connected, a single starting node exists, all branching points are merged again (especially for nodes defined as parallel or merging).

o Quality Assurance: the content of the model is quality checked before release, meaning that before a release can happen and approval by the designer is needed that the input is sufficient and appropriate. The above mentioned scenario “Walkthrough” is used to pre-check the model

o User Assignment: the model is assigned to a user/user group during release similar to a task assignment/delegation in group-ware systems

o Revision safety: the released state, assigned to a user-group is stored and not editable any more. In case that an update is needed, the previous version is archived and a new version is



assigned to users. Special consideration needs to fact that in case that learners already started their work a concept for transfer of evidence and progress is needed.

Execution Mechanism: during execution, functionality is integrated the supports the learner as well as the teacher in gathering information about progress and state. The execution mechanism provides the following functionality:

o Task and Progress Overview: the system provides an overview on currently running/assigned tasks including contextual information such as teacher, area, level etc. as an landing view.

o Start and Restart of Activity Sequences: each started process is represented in the system as an instance of an execution workflow. Functionality to start/stop/restart the instance is provided meaning the learner can stop a certain point and continue later. An open issue relates to ad-hoc activities introduced by the learner. A concept for this approach is to be developed.

o Delegation: The activities have assigned roles within the design, triggering an automatic task hand-over. This means that the interaction process between teacher and learner is also re-presented by the activity stepper

o Learning Services Trigger: Learning services (as defined above, such as tools, online media, resources) can be triggered from within the activity stepper. This trigger is realized as a hyperlink to the specific services.

o Evidence Collection: Evidence that a certain activity is completed by the learner is uploaded/fed back through the activity stepper to the Mahara environment

Profiling/Backend Mechanisms: as a backend of the system, the teacher has the chance to analyse continuously the progress of the student and provide immediate feedback if needed. The feedback can have the form of comments (as defined by specific tasks, delegated to the teacher) or validation of evidence.

o Progress View: the student progress is assessable from a time and content dimensions. The time dimension sets defined execution times of certain activities in context with real execution time by each student. From a content perspective, the evidence stored by students can be assessed and further analysed, establishing a read-interface for the teacher.

o Logging: All information from a time and interaction perspective is logged and provided as feedback to the teacher. Logging and mining mechanisms need to be integrated as needed.

5.3 Architecture

The architecture of NEXT-TELL and dependencies between components has been defined in D3.1 in the first year of the project. This architectural analysis provides a drill-down in that high-level architecture with respect to the NEXT-TELL Activity Stepper.



Figure 7 NEXT-TELL Activity Stepper Architecture

5.3.1 NEXT-TELL Metamodelling Platform

The NEXT-TELL Metamodelling Platform is based upon the ADOxx Metamodelling Platform and configured according to the needs of the project. The configuration is done from two aspects resulting in the kernel of the system:

NEXT-TELL ECAAD Library: represents the implementation of the modelling method as described in D2.1 and D2.3 respectively

NEXT-TELL ECCAD Repository: represents the storage and persistence view in the system

Functionality for access control and data access is provided by the platform in addition to a rich-set of functionality provided through the ADOxx Server. Within the following the focus lies upon the NEXT-TELL Activity Stepper, the ECCAD planner is mentioned due to the interdependencies between design and execution.



5.3.2 NEXT-TELL Activity Stepper Execution Engine

The NEXT-TELL Activity Stepper Execution Engine provides the functionality as defined above from an implementation perspective. All functionality is provided as a web-service to the external environment allowing an integration with external systems and other NEXT-TELL components. The two main building blocks are

Apache ODE: as the execution engine for the instances, Apache ODE takes over the responsibility to interpret and enact the models received from the ECAAD planner. The interpretation is using validation and verification mechanisms from graph-theory to determine if the model is executable. In addition functionality to “bind” services is included, since the operationalization of the sequence is not related to web-service and their orchestration but rather to a provision of information and access, the availability of all linked services is continuously checked. An important aspect is that the BPEL process deployed in Apache ODE is unaware of the actual content of the learning sequence but takes over the control and persistence aspects of the system

ADOweb Service Framework: provides the web-service access functionality of the component. The service framework allows to integrate external services such as Mahara for collection of evidence but also provides the functionality in the component as a webservice.

5.3.3 NEXT-TELL Activity Stepper User Interaction and User Interface

The user interaction and user interface components of the system are provided as a web-based system and are developed using standard technologies and frameworks. An important consideration is integretability of the system into existing portals and environments.

Figure 8 NEXT-TELL Activity Stepper Mock-up



6 e-Portfolio Integration

The NEXT-TELL e-Portfolio is the central evidence holding element used to create and store collections of artefacts to share with fellow students, teachers and peers as evidence of learning activity described in the Activity Stepper. It is also meant for meeting the needs of established and emerging pedagogy and approaches to learning like the reflective learning. In fact the NT e-Portfolio allows learners and teachers to reflect on their learning and experiences over a given period, for an assigned learning activity and/or the material produced for an assigned learning task.

The artefacts (like report, video annotations, audios file or a Google Docs) prepared in answer to a request of a learning activity and students’ reflections on the process and products according to the learning activity plan of the Activity Stepper are stored in the e-Portfolio as files or links to documents. Upon request or when needed, these files can be exported in e-Portfolio views or shared with the other students or teachers. In NEXT-TELL there are two ways to upload a file: manually (the student uploads the file from the file system) or via web-service depending on how available the information is to automatic capturing.

The latter option has been implemented by extending the adopted open source e-Portfolio system, Mahara, in order to allow to transfer and store artefacts (e.g. the chat text or video annotation) in the e-Portfolio which have been captured or generated in the other NEXT-TELL system components like Open Simulator or EVA.

Since it’s expected that an artefact created outside the e-Portfolio by the student X and uploaded via web-service to Mahara goes into the e-Portfolio owned by X, a mechanism for synchronising the accounts of the e-Portfolio and the others NEXT-TELL components is necessary. The next two paragraphs explain the single sign on implemented for the e-Portfolio and developed web-service used to upload external files to Mahara.

6.1 Mahara Authentication Service

Standard installation of Mahara does not support any mechanisms for the single sign on (SSO). An extension of Moodle installed for NEXT-TELL (see D3.2) allowed the smooth integration between Moodle and Mahara. However this SSO works only for Moodle.

In order to allow the integration of Mahara with any other NEXT-TELL components we implemented the SSO based on the Central Authentication Service (CAS) installed at JRS and currently adopted as the authentication service for all NEXT-TELL modules.

The CAS login complements and not replaces the existing login of Mahara.

Figure 9 shows the login page of NEXT-TELL Mahara where the new interface for the login via CAS is clearly highlighted in red.



Figure 9: Mahara e-Portfolio with the CAS

6.2 Import Web-Service

The import web-service (WS) of Mahara has been implemented to give the possibility to other NEXT-TELL applications to automatic upload files to the resource store private to user’s e-Portfolio whenever the student’s activity has produced some evidence of learning according to the activity plan suggested in the Activity Stepper (see the example in Figure 10).



Figure 10: Evidence of planned learning activities stored in Mahara

The WS does not distinguish the file format: any type of file (e.g. text, audio, image etc.) can be transferred to the e-Portfolio using this WS. Mahara recognizes the file extension and automatically categorises the file as text, image, video etc.

Since Mahara manages some file attributes like the name, file description and tags, the implemented web-service also allows external components to specify the same data in addition to the physical file to upload.

The technical details concerning how to use the import WS follow.

Name of the service:

mahara_portfolio_upload_file_user

Description:

Web-service to upload a file to Mahara resource store private to the user.

How it works:

The file must be a resource accessible via web and identified by a url.

The type of the file will be recognized using the “localfilename”.

The authentication method uses a token: with this token is only possible to upload files.

The parameters are passed through the POST method.

The produced artefact (the file) has to refer to the Activity Id specified in the Activity Stepper

Token used for NEXT-TELL Mahara: xyz

Call: http://research01.exact-learning.com/NEXT-TELL/artefact/webservice/rest/server.php?alt=json& wsfunction=mahara_portfolio_upload_file_user&wstoken=xyz



POST parameters:

username = <login-name of the user to upload file>

activityid = <the Id of the activity of reference in the Activity Stepper>

url = <url of the resurce to upload>

localfilename = <File name of the resource e.g. ‘management.pdf’ >

title = <Title of the resource>

description = <Description of the resource>

tags = <list of tags separated by comma >

The following example uses PHP and curl1 to call the WS and pass the parameters.

Example 1

The file will be uploaded in the section “My files” of the user “Demo”.

Example 2

1 curl is a command line tool for transferring data with URL syntax, supporting DICT, FILE, FTP, FTPS, Gopher, HTTP, HTTPS, IMAP, IMAPS, ...

$url="http://research01.exact-learning.com/NEXT-TELL/artefact/webservice/rest/server.php?alt=json&wsfunction=mahara_portfolio_upload_file_user&wstoken= xyz ";

$data = array(

"username"=>"demo",

“activityid” =>”001”

“url"=>"http://www.NEXT-TELL.eu/wp-content/uploads/2010/11/NEXT-TELL-D4-2-BHAM-Student_Model_Tools_R1_v07.pdf",

"localfilename"=>"NEXT-TELL-D4-2-BHAM-Student_Model_Tools_R1_v07.pdf",

"title"=>"Student Model Tool",

"description"=>"Workpackage 4: first version of the open learner model prototype",

"tags"=>"NEXT-TELL, workpackage, tools, "

);

$ch = curl_init();

curl_setopt($ch, CURLOPT_TIMEOUT, 10);

curl_setopt($ch, CURLOPT_URL, $url);

curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);

// POST

$body = http_build_query($data, '', '&');

curl_setopt($ch, CURLOPT_POSTFIELDS, $body);

curl_setopt($ch, CURLOPT_POST, 1);

$responseBody = curl_exec($ch);

$responseInfo = curl_getinfo($ch);

curl_close($ch);

echo $responseBody;



The result after the call of the web-service is shown in the next figure. It’s evident from the screenshot that the file has been correctly uploaded together with his attributes and tags.

Figure 11: Mahara My File after the call of the import WS

$url="http://research01.exact-learning.com/NEXT-TELL/artefact/webservice/rest/server.php?alt=json&wsfunction=mahara_portfolio_upload_file_user&wstoken= xyz ";

$data = array(

"username"=>"demo",

“activityid”=>”002”

"url"=>"http://www.bookhooks.com/resources/avocabo61_harrypotter.pdf",

"localfilename"=>"avocabo61_harrypotter.pdf",

"title"=>"Happy Potter Book",

"description"=>"Harry Potter and the philosopher's stone",

"tags"=>"readings, March 2012"

);

ch = curl_init();

curl_setopt($ch, CURLOPT_TIMEOUT, 10);

curl_setopt($ch, CURLOPT_URL, $url);

curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);

// POST

$body = http_build_query($data, '', '&');

curl_setopt($ch, CURLOPT_POSTFIELDS, $body);

curl_setopt($ch, CURLOPT_POST, 1);

$responseBody = curl_exec($ch);

$responseInfo = curl_getinfo($ch);

curl_close($ch);

echo $responseBody;



6.3 Future Work

Two parallel streams of work on Mahara will start aiming at reinforcing the concept of integration between the e-Portfolio module and the other project components and supporting the teacher’s analysis of students’ learning activities.

With respect to the first activity, the aim is to complete the integration between Mahara and the Activity Stepper in order to store the list of planned activities and related evidence defined in the Activity Stepper in the student’s e-Portfolio.

The basic idea is to create a new Mahara View2 every time a new Plan in the Activity Stepper is instantiated

with a list of suggested learning activities for each of them the student is asked to provide evidence. At the beginning this View will be empty. As soon as a new learning activity is complete the evidence is uploaded to the student’s e-Portfolio using the web-service described in the previous paragraph and the View is filled with the produced artefact (see the example in Figure 12).

When all the learning activities are complete the dedicated View is also automatically finalised in Mahara and ready to be shared with the teacher.

However, the teacher will have access to the View for an assigned Plan at any time, even if incomplete, in order to monitor the progresses of the student.

2 In Mahara a View is a collection of Artefacts. Views give students a way to display their artefacts to the people (e.g. the teacher) they want to see them.



Figure 12: Automatic creation of a Mahara View with evidences of planned activities



A new web-service will be developed to import (and store in the e-Portfolio) the following information3 related

to the student plans:

As far as the second activity is concerned, the aim is to provide the teacher with a new Mahara interface to search for evidence of learning activities of a student or a controlled group of students stored in the e-Portfolio. That will allow the teacher to monitor the (learning) progress of the single or a controlled group at any time without waiting the student or group of students decide to share the Mahara View for the assigned plan and list of activities.

3 The exact list of data to be collected is under definition at the moment of writing

CAS username (of the student)

Plan name

Plan description

o Activity1 name

o Activity1 description

o Activity1 Id

o Activity2 name

o Activity2 description

o Activity2 Id

o ….



7 V isualisation of Learning Activities

This section provides some details of the activity visualisation scenario to be prepared for implementation in the second release of the NEXT-TELL toolset. This is a Moodle forum and chat scenario. Use cases and scenarios for T3.2 being currently developed will include consideration of a theoretical motivation derived from Crawford et al's (2008) Cognitive Density framework. This conceptual development will be included in M24 deliverables.

7.1 Moodle Chat Visualisation

The Moodle chat visualisation scenario is the first scenario being developed towards implementation. Forums and chatting facilities are increasingly used in Moodle and other content management systems. They are used in a variety of subjects, often to support or consolidate ongoing learning. NEXT-TELL Moodle chat visualisations in this scenario are intended to provide support to teachers in promoting discussion and self-reflection among students learning English as a second language. One of the great elements of Moodle chat for NEXT-TELL is that students who do not share a common first language can text chat in English.

This scenario will involve interacting within a forum, capturing and visualising part of threads, or chatting using a dialogue box in a instant messaging style.

7.1.1 Chat Scenario Interaction Metrics

Elements of data in a chat scenario to be represented:

number of chat/forum entries

number of chat/forum entries (Param: filter criteria, e.g. subgroup)

length of each chat/forum entry

length of each chat/forum entry (Param: filter criteria, e.g. subgroup)

length of chat/forum thread

total length of all entries

time of engagement (e.g. timeline, graph showing level of engagement) etc.

number of reciprocating responses in chat between two users

This data items can be formed into generic categories:

number of data points

correlation of preceding data point

key words, frequent words

time at which interactions took place

How should these data items be represented? In our first development iteration we will be implementing activity timelines, histograms, and progress meters. Then in subsequent iterations we will be implementing work clouds and network graphs (see Table 1).

YES timeline/sparkline/graph

? state graph/model/diagram

YES histogram/bar chart

YES progress meters



YES word clouds

? correlation plots (e.g. bubble)

YES directed/network graphs

Table 1: Visualisation types planned for Moodle forum and chat visualisations

Activity time-lines will show who made contributions and at what time these contributions were made. Histograms will represent how many contributions were made. These may represent number of posts, or number of words. Progress meters will represent progress towards some target, which might be a word count-target or numbers-of-posts target. In the second development iteration progress meter targets might be in terms of the groupings or identity of others users. For example, a progress meter can show progress towards a student meeting a target of interacting with someone from every sub-group (for example a Norwegian student may have a target to interact with a student from every participating Austrian school).

In the second development iteration words clouds will be used to represent the frequency of words used. This will visualise word clouds for individuals, groups and all users. So teachers and students will be able to visualise differences in the frequencies of particular words used between individuals and groups, and between groups (such as Norwegian and Austrian students). In this second development iteration direct graphs will also be created which will visualise the network of responses between individuals.

Further developments may also involve some minimal semantic interpretation of text. For example,

docuburst4 may be used to word frequencies and simultaneously show relationships between words.

7.1.2 Use Case

A number of similar use cases are likely to be developed into more detailed scenarios to aid system evaluation. Here is an initial NEXT-TELL Moodle chat use case to focus development priorities:

Title: TESL: Moodle chat/forum feature is used for students to gain experience of communicating with English speakers in other countries.

Goal: Students practice writing English with another student of a different nationality

Initiating: Teacher

Affect: Student, Peer, Teacher

Start Conditions: Students in Austria and students in Norway are available to chat online in real time. All are seated individually at a computer.

End Result: In interaction has occurred. Statistics are generated about students’ participation in the interaction.

Normal course for the use case:

● A discussion topic is given to students e.g. discussion of events in recent Open Simulator interactions.

● Students are paired up or join larger groups Students can talk to anyone they choose in the groups they are put in Interactions are 1 on 1, or many to 1

● An interaction occurs between the assigned students. This is recorded, and real time statistics are

produced about the nature of the interactions. These are made available in BHAM’s software,

● Statistics are used post-session (by the teacher/student/peer) to evaluate what students did in

4 http://faculty.uoit.ca/collins/research/docuburst/index.html

http://faculty.uoit.ca/collins/research/docuburst/index.html



















terms of the learning objectives.

Exceptions: Technology failure

Data Content:

Statistics/Activity Visualisation:

Each metric is to be given as a summary, and broken down by student and (nationality) group.

The filter mechanism on BHAM’s browser software will be adapted to do this.

a) Without considering the content of the text in the chat:

LEVEL OF ACTIVITY

Total number of chat entries

Total number of words used

Distribution of number of words used per entry

Time at which a line of the chat is sent

Intensity of chat interaction

SOCIAL NETWORK

Map of which students regularly communicated with each other

b) Including the content of the text:

INFORMATION CONTENT

Most frequent words

Keywords (possibility of semantically linking them in the visualisation?)

Formative Assessment Purpose:

Further questions the data may be used to answer, examples:

Was the conversation alternating

To what extent did the conversation occur

Did the students answer given questions? Are they able to engage in a conversation in terms of asking questions / answering questions

Competencies/Learner Model Content:

Nothing is immediately considered in this example.

7.1.3 Available Data

Table 2 presents typical data elements to be captured and processed for each chat entry:

Data Field Example Data

User identity (communicator) 1067

User identity/identities (recipient(s)) 1093, 1074, 1201

Timestamp 2012-02-02:12:26:18

Textual content “I like interacting in Second Life”

Metadata

Length of entry (wordcount) 6

Table 2: Raw data elements



7.1.4 Activity Process Visualisation

Common queries will draw on the same information to be interpreted in different ways. Filtering information to make response to a query will be done on BHAM’s software interface, post data capture and processing. Information will be available at different levels of abstraction for a selection of students: either the whole group, or for a multi-selected sub group. For a given selection, a summary will be shown and a break down by student.

Filter mechanism

The filter parameters will allow specific groups and students to be selected for a given activity (no competencies will be recorded in this example, as there is no automated inference mechanism). The existing filter mechanism will be updated to allow multi-select, and maybe the additional inclusion of other parameters (according to stakeholder requirements). Figure 13 presents the current filter interface.

Figure 13: Filter interface

Summary and breakdown

Information may be broken down in different ways, for a given set of filter criteria. For example, for a specific activity. Figure 14 shows a visualisation for summary and breakdown.

Figure 14: Example summary and breakdown

Visualisations of type: “LEVEL OF ACTIVITY”

These are achievable with current implementation of BHAM’s software with minor adaptations. As discussions are a two way process, we will consider incoming data, in addition to outgoing data, for each student. This will allow information to be deducted, such as whether the conversation was one sided. The four example (simple) visual methods to initially be used for this purpose are:

Tallys (for number of lines/entries and number of words)



Histograms (for showing the lengths of lines of chat)

Timeline (to show when chats lines occurred)

Graph (to show hotspots and periods of intense interaction)

Figure 15 shows prototype visualisations for moving averages and timelines. Note that two calendars are used to set the time-range to be visualised.

Figure 15: Example of Moving average and timeline visualisations, with calendars setting out start and stop dates



8 Conclusions

This deliverable has presented the revisions and extensions of the methods and specification for activity capturing for the second prototype of the NEXT-TELL system. Updates on the focus area for this second release have been given along with a discussion of the minor architectural changes. Further details have been given on the activity capturing from various environments, the activity stepper, the tighter integration with the e-Portfolio and the visualisation of learning activities. These revised and extended specifications provide a guideline for the realisation of the second prototype.



9 References

[Apache, 2011] Apache Software Foundation (2011). Apache Rave (Incubating). <URL: http://incubator.apache.org/rave/>

[Crawford, 2008] Crawford, V. M., Schlager, M. S., Penuel, W. R., & Toyama, Y. (2008). Supporting the art of teaching in a data-rich, high-performance learning environment. In E. B. Mandinach & M. Honey (Eds.), Data-driven school improvement (pp. 109-129). New York: Teachers College Press.

[W3C, 2011] W3C (2011). Widget Packaging and XML Configuration. W3C Recommendation 27 September 2011. <URL: http://www.w3.org/TR/widgets/>

[W3Schools, 2012] W3Schools (2012). Browser Statistics. Retrieved on 2012-03-12 <URL: http://www.w3schools.com/browsers/browsers_stats.asp>

[Wikimedia, 2012] Wikimedia Foundation (2012). Usage share of web browsers (Source StatCounter). File retrieved on 2012-03-12 <URL: http://en.wikipedia.org/wiki/File:Usage_share_of_web_browsers_%28Source_StatCounter%29.svg>

http://incubator.apache.org/rave/

http://www.w3.org/TR/widgets/

http://www.w3schools.com/browsers/browsers_stats.asp

http://en.wikipedia.org/wiki/File:Usage_share_of_web_browsers_%28Source_StatCounter%29.svg

http://en.wikipedia.org/wiki/File:Usage_share_of_web_browsers_%28Source_StatCounter%29.svg



10 Glossary

Terms used within the NEXT-TELL project, sorted alphabetically.

BSCW The document store used in NEXT-TELL used for storing internal documents

Document store see BSCW

EuresTools The reporting tool used in NEXT-TELL

PM Person month

T Task

WP Work package

Partner Acronyms

JRS JOANNEUM RESEARCH Forschungsgesellschaft mbH, AT

UniRes UNI RESEARCH AS, NO

KMRC Medien in der Bildung Stiftung, DE

TUG Technische Universität Graz, AT

CBS Copenhagen Business School, DM

BHAM University of Birmingham, UK

IOE Institute of Education, University of London, UK

EXACT eXact Learning Solutions SPA, IT

TALK Verein offenes Lernen, AT

BOC-AT BOC Asset Management GmbH, AT

BOC-PL BOC Information Technologies Consulting SP.Z.O.O., PL

MTO MTO Psychologische Forschung und Beratung GmbH, DE

Abbreviations

BS Baseline Study

CbKST Competence-based Knowledge Space Theory Training Course

CBT Computer Based Training

DBR Design-Based Research

ECAAD Evidence Centered Activity and Appraisal Design (builds on the ECD)

ECD Evidence Centered assessment Design (e.g. PADI project)

EFL 'English as a Foreign Language'; EFL refers to learning English in a non-English-speaking region, such as studying English in an Asian or Latin American nation. Typically, EFL is learned as part of a student's school curriculum or for career purposes if working for an international corporation.

ENA Epistemic Network Analysis

ESL English as a Second Language; refers to learning English in the target language environment

HCI Human Computer Interaction

ICT Information and Communication Technology

IT Information Technology

LEPP Longitudinal Evaluation of Performance in Psychology (2nd generation e-Portfolio)

NEXT-TELL Next Generation Teaching, Education and Learning for Life

OLM Open Learner Model



PADI The PADI project aims to provide a practical, theory-based approach to developing quality assessments of science inquiry by combining developments in cognitive psychology and research on science inquiry with advances in measurement theory and technology.

RA Requirement Analysis

RDS Researcher-led Design Study

SRI Stanford Research Institute

STEM The Science, Technology, Engineering, and Mathematics (STEM) fields are collectively considered core technological underpinnings of an advanced society, according to both the National Research Council and the National Science Foundation

TDS Teacher-led Design Study

TEL Technology Enhanced Learning

TESL Teaching English as Second Language

TISL Teachers Inquiry into Students Learning

Acknowledgement: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 258114.