Scenario-based e-Learning

Todorka Glushkova, todorka.glushkova@gmail.com6-th WorkShop SEERE, Ravda’06

Application of templates and models for

SE e-learning

Best Practice Guide for content developers, Carnegie Mellon University

Structure of the e-content; Planning and standardization in the e-Lesson

development process:- structure of development team; - identification of materials; - sharing and storage of SCOs into Content Repositories;

Determination of SCOs. Structure and creation of tests. Sequencing and navigation; Templates and models.

The main goals

To look at the main 10 templates of the Best Practice guide

To parameterize them and create a series of different templates according to didactic aims (Goals &Tasks Model);

To create a series of models for the structure of e-learning packages.

Template 1 “Single SCO, single asset”

This is the main structure. Root Aggregation (RA) contains one SCO and one asset.

Using: The template can be used as a part of different models.

Content structure diagram:

Rules:BEHAVIORS SCORM FUNCTION

1. To complete RA the learner must complete the SCO

Rollup: All: satisfied, completed

The template 2 can be used in the creation of learning resources with a single structure, containing some Assets – pictures, graphics, music… and a final test. The LMS doesn’t use the results from the test but the system stores them for future analysis.

We can parameterize the template by the following parameters:

- number_of_assets – type Integer, default value is 4 and number_of_asset=number of questions in the test -1.

- Has_test – type Boolean, default value=“Yes”.

Template 2 “ SCO with assets”

If we use default values of the parameters: Pattern_2(4,yes).

We mark that Pattern_1=Pattern_2(1,no)

BEHAVIORS SCORM FUNCTION

1. To complete RA the learner must complete the SCO

Rollup: All: satisfied, completed

2. To complete the SCO it must complete the test in Asset _number_of_assets

No SCORM Function

The template 3 includes one SCO with a set of links. In the LMS this structure is called “The Black Box”

We can use this template to present new knowledge when the learner must to achieve a perfect test score.

This template presents a typical CBT lesson. We can transform every CBT-lesson to SCORM-based

using this template. The actions from “The Black Box” are not Sequenced

and they don’t describe the rules and are not managed by the LMS. We can parameterize the template in a similar way as Template_2. By using of default values:

Pattern_3(4, yes).

Template 3 “The Black Box”

BEHAVIORS SCORM FUNCTION

1. To complete RA the learner must complete the SCO

Rollup: All: satisfied, completed

The template 4 includes two SCOs in the RA that are instances from Template 2.

We can parameterize this template as:- Number_of_SCOs -(default value is 2);- (SCO_num, Pattern_num). For example (1, 2(3, yes)) means that the first SCO is an instance of Pattern_2(3,yes).

Template 4 “Multiple SCOs with Assets ”

BEHAVIORS SCORM FUNCTION

1. To complete the RA must complete all of SCOs.

RA:Rollup: All: satisfied, completed

2. To complete all of SCOs we must complete successfully all of tests from Asset-(number_of_assets) for every SCOs that has_test =yes.

No SCORM Function

3. The learner don’t start SCO_n while SCO-(n-1) is not complete, n≤(number_of_SCOs)

SCO-(n-1): If not complete, Deny Forward Progress

4.The learner can return to the previous SCOs at any time.

RA: Forward only = false

This template allows a learner to get additional information from informational SCOs when he makes a mistake on a SCO-test. The LMS manages this process with the Objective mechanism.

We can parameterize this template:- Number_of_SCOs – (default value is 3);- Has_test – (default value “Yes”). When Has_test=“yes”, the Questions= (Number_of_SCOs – 1)= number of Objective variables. - (OBJ_n, min_value_n), (n< Number_of_SCOs).- (SCO-n, pattern_num ), n< Number_of_SCOs and pattern_num<5. Default value (SCO1,pattern_2(1,no)); (SCO2,pattern_2(3,no)); - Set (SCO_Number_of_SCOs(Asset_k); OBJ_k), к<Number_of_SCOs.- Read (SCO_k, OBJ_k)

Template 5 “Remediating Using Objectives”

BEHAVIORS SCORM FUNCTION

1. To complete RA must completethe Post-Test from SCO- (Number_of_SCOs)

RA:Rollup: All: satisfied, completedAll SCO-k: isRolledUp=false, k< Number_of_SCOsSCO- (Number_of_SCOs): isRolledUp=true

2. Learner must complete SCO-(k-1) before SCO-k, k< Number_of_SCOs

RA: Flow=true;Choice = false

3. To complete SCO- Number_of_SCOs must pass all OBJs

No SCORM Function

4. If make a mistake of OBJ-k read SCO-k SCO- (Number_of_SCOs): set OBJ-kSCO-k:skip if OBJ-k passed

5. Allow 2 attempts for every SCOs All SCOs : Attempt Limit=2

6. The learner has 2 attempt to pass the Post-test No SCORM Function

This template allows us to use a pre-test and a post-test. According to the answers of students from the pre-test, OBJs are passed or failed. If the student passes the pre-test he can pass to post-test; if he makes a mistake he must see the informational SCOs. LMS doesn’t manage results from the post-test.

We can parameterized this template:- Number_of_SCOs.- Has_pre_test- default value is “yes”.- Has_post_test- default value - “yes”.- (OBJ_n, min_value_n), (n<= Number_of_SCOs).- (SCO-n, pattern_num ), 1<n<= Number_of_SCOs+1 and pattern_num<=5. [(SCO-2,pattern_2(0,no)); (SCO-3,pattern_2(0,no))]; - Set (SCO-1(Asset-k); OBJ-k) Default values: Set(SCO-1(Asset-1),OBJ-1), Set(SCO-1(Asset-2), OBJ-2)- Read (SCO-k+1, OBJ-k) Default values: Read(SCO-2,OBJ-1), Read(SCO-3,OBJ-2).

Template 6 “Pre- and Post-Test Sequencing”

Example: Topic “Introduction to SE”• Number_of_SCOs=9;• Has_pre_test=”yes”;• Has_post_test=”yes”;• (OBJ-n,1);• (SCO-n,pattern_2(0,no)), 2<n<10;• Set(SCO-1(Asset-k); OBJ-k), 1<k<9;• Read(SCO-k+1, OBJ-k), 1<k<9;

Aggr1Topic 1

SCO-1Pre-test SCO-2 SCO-3

SCO-4 SCO-5SCO-6

OBJ-1 OBJ-5OBJ-2 OBJ-4OBJ-3 OBJ-6 OBJ-7 OBJ-8 OBJ-9

SCO-7 SCO-8SCO-9 SCO-10

SCO-11Post-test

Asset11_1 Asset11_

2

Asset11_3

Asset11_4

Asset11_5

Asset11_6

Asset11_7

Asset11_8

Asset11_9

Asset-1 Asset-2

Asset-3 Asset-4

Asset-5 Asset-6

Asset-7 Asset-8

Asset-9

The informational SCOs are grouped in a separate Aggregation. The learner must give answers to the test-Items from the pre-test. If he makes a mistake he must see the respective informational SCOs from the Aggregation. Finally, he must make a post-test. The LMS manages the results from pre- and post-tests by OBJs.

The parameterization of the template is similar to Temlate 6.

Template 7 “Pre- and Post-Test Sequencing – 2”

• Example 2: For the same topic, if we group informational SCOs (from SCO3 to SCO11) in Aggr-B:

Aggr1-RATopic 1

SCO-1Pre-test

Aggr-BSCO-2

Post-test

Asset10

Asset11

Asset12

Asset13

Asset14

Asset15

Asset16

Asset17

Asset18

Asset-1 Asset-2

Asset-3 Asset-4

Asset-5 Asset-6

Asset-7 Asset-8

Asset-9

SCO-3 SCO-8

SCO-4 SCO-9

SCO-5 SCO-10

SCO-6 SCO-11

SCO-7

OBJ-1 OBJ-8OBJ-2 OBJ-6OBJ-3 OBJ-4 OBJ-7 OBJ-9OBJ-5

OBJ-10 OBJ-11

OBJ-12

OBJ-17

OBJ-15

OBJ-13

OBJ-14

OBJ-16

OBJ-18

The template 8 allows the LMS to control the access of the learner to the final test. He can’t pass to it if he hasn’t completed the learning process in Aggr 1. The LMS manages the results from the tests by OBJs.

Template 8 “Remediating Using Objectives – 2 ”

The parameterization of the template:• Number_of_SCOs . • Has_test- if the value is “No”, the Pattern_8 is similar of Pattern_2 (Asset-

>SCOs; SCOs->Aggeregations). -Att_Limit –max number of attempts in the final test.-(OBJ_n, min_value_n), (n<= Number_of_SCOs).- (SCO-n, pattern_num), n<= Number_of_SCOs. Default values (SCO-1,pattern_2(1,no)); (SCO-2,pattern_2(3,no)); - Set (SCO-last(Asset-k); OBJ-k), к<=Number_of_SCOs, last=(Number_of_SCOs+1). Default values: Set(SCO-3(Asset-1),OBJ-1), Set(SCO-3(Asset-2), OBJ-2).- Read (SCO-k), OBJ_k), к<=Number_of_SCOs.

• Example 3: The topic “Management of the software quality” :- Number_of_SCOs=4;- Has_test=”yes”;- Att_limit=3;- (OBJ-1,0.7);(OBJ-2,0.7);(OBJ-3,0.7);(OBJ-4,0.7)- (SCO-1, pattern_2(0,no)); (SCO-2,pattern_2(3,no)); (SCO-3, pattern_2(0,no)); (SCO-4,pattern2(0,no)).- Set (SCO-5(Asset-k), OBJ-k) за k=1,2,3,4.- Read(SCO-k, OBJ-k) за k=1,2,3,4.

RATopic 4

SCO-5-TestAggr.1

SCO-1 SCO-3

SCO-2 SCO-4

Asset-1

Asset-2

Asset-3

Asset-5-1

Asset-5-2

Asset-5-3

Asset-5-4

OBJ-1 OBJ-2 OBJ-4OBJ-3

We can use the intra-SCO rules that are similar of the traditional CBT lessons. According to the choice of the learner, OBJ set a value from [ -1;1] and the LMS branches out the learning process according to this value. We could make a parameterization of the template according to the number of choices.

Template 9“Basic Three-Way Branching”

Template 10“Pre- and Post-Test Sequencing with New

Content for Remediation ”

We can use this template in the final stage of the learning process for control of the student’s knowledge. According to the behavior of the learner and the result from the pre-test, he can pass directly to the final test or see additional information and take the final test again.

The parameterization:

- Num_SCOs_A

- Num_SCOs_B, OBJs=(Num_SCOs_A+Num_SCOs_B)=n

- (OBJ_n, min_value_n), n=(Num_SCOs_A+Num_SCOs_B).

-(SCO-k, pattern_num), k<=n

-Set (SCO-A; OBJ-p), p<=Num_SCOs_A.

-Set (SCO-C; OBJ-p), Num_SCOs_A<p<=Num_SCOs_B.

- Read (SCO-k, OBJ_k)

The models

We could make different combinations from templates and structure various learning resources as e-lessons, e- courses, e-packages.

By parameterization of the templates and the models we can generate various different e-learning resources according to the educational aims and tasks of the authors of e-content.

The Best practices Guide for Content Developers proposes some basic models.

Model“Remediation Multiple Aggregation ”

Model“Mastery Testing Multiple Aggregations ”

Model“Pre-Post-Testing Sequencing with

Aggregations”

Model“Traditional CBT-Branching with Multiple

Decisions ”

Conclusions

The parameterization of the basic templates from the Best Practice Guide allows us to create different variants of e-learning resources;

The change of the abstract level in the templates and models allows for generation of different levels of e-content: lessons, modules, courses, packages.

Communication between authors and the system for determination of the values of parameters allows the system to generate dynamically the concrete model of e-content.

The plans and future work

To develop a model for interactions between educational aims and the set of templates and models. (When the author defines the aims of the teaching, the system will suggest the most suitable templates and models for creation of e-content-PA).

To develop a XML-based language for describing of the patterns, models an learning scenarios.

Thank you for your attention.