A Web Application for Aiding Tutors to Develop Course Outlines

Nikolaos Spanoudakis, Evangelia Krassadaki, Aliki Pialoglou and Nikolaos Matsatsinis

Decision Support Systems Lab (ERGASYA), School of Production Engineering and Management, Chania,

Technical University of Crete, 73100, Greece

Keywords: Higher Education, Quality Assurance, Course Outline, Learning Outcomes, Bloom’s Taxonomy of

Learning, Generic Skills, Student Assessment, Web Application.

Abstract: In 2011, the Hellenic Quality Assurance and Accreditation Agency prepared and distributed a course outline

template, in paper format, to be filled in by the university tutors. This template contains details about

learning outcomes, generic skills, teaching and assessment procedures for each course. The teaching staff,

having little knowledge on the aforementioned topics, faced serious difficulties in filling it in. Thus, we

developed a web-based information system for outlining courses in our institution. It guides the user (tutor)

step-by-step to properly record, document and store every detail of a course, and export it to a pdf file.

Additionally, by recording the information in a database, it allows any kind of queries, thus it offers various

statistics in university/school/departmental level on the usage of verbs of the Bloom’s taxonomy, about the

nurtured generic skills, about the students’ workload per course, etc. The system is user-friendly, according

to the results of a short survey, and it is fully expandable. This paper focuses on the presentation of the web-

based system application along with the benefits it introduces firstly for the tutors and secondly for the

quality assurance team of the university.

1 INTRODUCTION

Quality assurance in the Greek higher education was

specified by virtue of Law 3374/2005, whereby a

single, nationwide ongoing evaluation process was

established, aimed at recording, analysing and

systematically assessing teaching and research work,

study programmes and other services of higher

education institutes (Eurydice network,

https://eacea.ec.europa.eu/national-policies/eurydice).

The same Law established the Authority for

Quality Assurance and Accreditation Agency in

Higher Education (HQA or ADIP in Greek), which

is the competent body for implementing quality

assurance in higher education. HQA’s mission is to

periodically certify the quality of higher education

institutions, of both the internal system of quality

assurance developed in higher education institutes,

and, the study programmes of all three cycles of

higher education, which are offered by academic

units. Recently, Law 4009/2011 established a

nationwide accreditation system, which follows

internationally acceptable qualitative and

quantitative criteria along with the guidelines and

indicators specified by the European Area of Higher

Education.

Within the frame of the last Law, the HQA

prepared a course outline template. This template, in

paper format, along with few guidelines and some

examples were distributed to every quality assurance

unit at university level. The local units, in their turn,

distributed the material to every teaching member of

the academic community.

However, what was missing was an awareness of

the professors and tutors towards these new quality

assurance issues like, using Bloom’s (1956) taxono-

my of educational objectives in cognitive domain to

express learning outcomes, introducing generic

skills and demonstrating their enhancement via

teaching and assessment methods, techniques and

practices applied etc. In other words, this initiative

introduced a new challenge to Greek Universities, a

competency-based reformation of curricula, as the

current international trend is. In fact, the endeavour

to enhance employability skills through higher

education studies is not unique in Greece.

Similar efforts are also outlined in reports from

other countries, including the Spellings

Commission’s report in the United States (Spellings,

2006), the Dearing report in the United Kingdom

(National Committee of Inquiry, 1997), and the

Bradley review in Australia (Bradley et al., 2008).

Spanoudakis, N., Krassadaki, E., Pialoglou, A. and Matsatsinis, N.

A Web Application for Aiding Tutors to Develop Course Outlines.

DOI: 10.5220/0007715003230330

In Proceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019), pages 323-330

ISBN: 978-989-758-367-4

323

This obvious difficulty of the academic staff

drove us to develop a web-based application for

tutors, who would like to fill-in their courses’ outline

in a safer environment instead of the paper format,

where faults and misunderstandings could occur.

Moreover, our system allows extracting information

in university/school/departmental level on all the

documented elements, such as the usage of verbs of

the Bloom’s taxonomy, the enhancement of generic

skills, the students’ workload per course, etc.

To assess the user-friendliness and acceptance of

the system we were aided by volunteers, tutors in

our university, who used the system and responded

to a short survey.

In this context, this paper is organised as follows:

the second section briefly presents the background

on the quality assurance process application in

Greece that motivated this work. Section three

presents the system architecture and then, in section

four, the evaluation and application first results are

discussed. Finally, some concluding remarks are

given in the last section.

2 BACKGROUND

The HQA, as an independent authority, supervises

and supports the Higher Education Institutions

(HEIs) in order to implement processes for the

assurance and continuous improvement of quality.

According to Law 4009/2011, which introduces the

main principles of accreditation, the HQA among

others, prepared a template for courses outline.

The course outline template is divided into five

(5) sections (https://www.adip.gr/en/accreditation-

docs.php). The first one contains some general

information about a specific course, which can

easily be completed by academics.

The second section of the template is devoted to

the learning outcomes and generic skills that a

specific course offers. The completion of this section

of the template requires deep knowledge and

expertise. The third section is devoted to the syllabus

of a specific course.

The fourth section of the template examines the

teaching and learning methods as well as the

assessment procedures that tutors apply for the

evaluation of the students’ performance. Thus, the

following information is requested: (a) the type of a

course’s delivery, as a face-to-face or a distance

learning, etc. (b) the ICT usage in teaching/learning

process, and (c) the teaching methods applied, like

lectures, seminars, etc. For this last component (c)

tutors have to declare the activities of students and

the total work-load in hours during the semester. The

students’ study hours for each learning activity have

to be given as well as the hours of non-directed

study, according to the principles of the ECTS. This

means that a tutor who is teaching a course of 5

ECTS has to declare 125 hours per semester divided

in specific activities for students, e.g. lectures: 26

hours, laboratories: 26 hours, group project: 23

hours and self study (study at home): 50 hours.

Moreover, in the same (fourth) section the tutors

have to clarify the methods of evaluation for the

summative procedures.

Lastly, in the fifth section of the template, the

suggested bibliography, books and journals, are

required to be filled-in.

However, according to the HQA's Annual Report

of 2015, where 28 thousands of courses outlines at

36 HEIs across the country were taken into account,

the documentation is totally incomplete (HQA,

Annual Report 2015). The shortcomings are mainly

focused on the second section of the template, which

refers to the Learning Outcomes & generic skills and

at the fourth

section, which concerns the teaching

and assessment methods applied. Indicatively, at 24

HEIs out of 36, the courses’ outlines have been

completed, with various completion percentages,

varying, e.g. in two Institutions, from 72.8% to

1.2%, respectively. Finally, in 10 Institutions no

course outlines were completed.

The findings of the Report for the crucial fields

of learning outcomes saw a very high deviation from

the goal of completely documenting all the under-

graduate programmes. The rate of completion in the

majority of under-graduate programmes is less than

40%, while in a significant number of Institutions it

is less than 5%. Similarly, in the teaching and

assessment section, most courses outlines are far

beyond the initial goal of full completion, the

highest rate of completed outlines is around 55% (in

management schools).

Pioneers in the whole effort among the Greek

HEIs are the technological and management schools,

while engineering schools are still far from reaching

this goal.

In this frame, in 2017 the local quality assurance

team of the Technical University of Crete distributed

the course outline template aiming to provide this

information to HQA. The above difficulties, as set

out in the Annual Report of the HQA (2015), also

manifested during the form completion (in paper

format) process. Our feeling is that the completion

of the form was treated as an extra bureaucratic

work, given the low degree of ownership of the

concepts of quality in tertiary education.

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Bee Bee Sng (2008) came to the same

conclusions in the case of Singapore HEIs

reformation, where there was an inadequate

preparation of teaching staff to adapt to rapid

educational changes. Educational changes affect

academics in more than one ways, the reader is

referred indicatively to Fullan (1991), Ford et al.

(1996).

In order to address the shortages of teachers'

knowledge and experience, as well as the limited

time they have for any work beyond research and

teaching, the authors, based on their research

interests (Krassadaki and Matsatsinis, 2012; 2017;

Krassadaki, et al., 2017; Krassadaki et al., 2014,

Spanoudakis et al., 2017) and previous experience,

designed and implemented a web-based application.

Our main goals are (a) to help tutors in the

syntax of the learning outcomes by adopting the

simpler format of using one verb of the Bloom’s

taxonomy per sentence, according to the literature,

(b) to develop a database of verbs based on the

Bloom’s taxonomy, (c) to develop a database of

various generic skills, (d) to create some controls i.e.

comparison of the ECTS per course with the work-

load of students, comparison of the learning

activities with declared generic skills, etc, so that the

information given is validated and ready to be

examined by the quality assurance team.

3 THE WEB APPLICATION

The system was developed using state-of-the-art

technologies for web applications. The model-view-

controller (MVC) software architecture (Leff and

Rayfield, 2001) was employed, as it offers the

possibility to reuse objects and is easily extensible.

We used the PHP programming language with

Javascript, combined with SQL statements for

querying and updating the database.

3.1 System Architecture

The system Architecture is presented in Figure 1 and

shows that a user can access the system with an

internet browser application. The system executes on

a web server and also employs an SQL database. To

deploy our system we used the XAMPP platform

(www.apachefriends.org), a free distribution, which

employs the Apache web server and the MySQL

database. All used components are open source, thus

they adhere to all modern standards and are safe for

their use.

View

Templates, Layout

Controller

Model

Database

2. demand

4. data

1. Request

HTTP

6. Response

HTML, CSS,

Javascript

3. Query

SQL

Browser

Web server

Apache

PHP

Database server

MySQL

Figure 1: MVC model and System Architecture.

The most important aspect of our system

architecture is the relational database specification

that gives it some important properties and that

allows to extract information about the course

learning outcomes.

3.2 Data Management

The database schema is provided in the form of an

Entity-Relationship (ER) Model (Bagui and Earp,

2004; Chen, 1976) in Figure 2 the major entities are:

• courses, whose major attributes are their name

and key. There are other attributes and

relationships that are hidden in the diagram as

they would clutter it and are not related to the

main points of this paper, however, for

completeness we name a few such as the tutor,

teaching hours, department of school, pre- or

post-graduate course type, teaching hours and

credits, etc,

• activities, whose name indicates their type,

such as participating to lectures, undertaking

projects, following laboratory classes,

seminars, studying, etc,

• skills, whose name indicates a generic skill

(Bennett et al., 2000). We will use generic

skills to refer to skills and competencies that

are beyond disciplinary knowledge and which

can be applied broadly across different

contexts, like decision-making, teamwork,

production of new research ideas, project

design and management, respect for diversity

A Web Application for Aiding Tutors to Develop Course Outlines

325

and multiculturalism, respect for the natural

environment, demonstrating social,

professional and ethical responsibility,

exercise of criticism and self-criticism, written

communication, oral communication,

leadership, initiative, time management,

problem solving, etc, Other terms, such as

transferable skills, employability skills,

general competences and key competencies,

have also been used in the literature to refer to

the same concept.

• assessment categories, such as projects,

written examinations, laboratory reports, etc.

Some of them have:

o sub-categories, for example a written

examination can have multiple choice

questions, or problem solving questions,

while a team project may have an oral

examination, or a public presentation.

• verbs, whose names are verbs that have been

classified according to the Bloom’s taxonomy

of learning (Bloom, 1956). Classification

attempts have produced various lists at

international level, the list of the Teaching and

Educational Development Institute of the

University of Queensland (1996) has been

used herein, and,

• levels, that refer to Bloom’s different levels of

learning for knowledge (level 1),

comprehension (level 2), application (level 3),

analysis (level 4), synthesis (level 5), and,

evaluation (level 6) (Bloom, 1956).

Relationships connect the entities and only in the

case of a course has verbs relationship (bottom-left

of Figure 2) do we use an attribute, one, though, that

is important, the sentence created using the

connected verb.

An important aspect of the database architecture

is the relationships shown on the top of Figure 2, i.e

. the activities nurture skills and the categories

validate skills. When tutors add generic skills to

their courses, e.g. team working, then they are

prompted to add activities that nurture them, e.g.

team project, and assessment methods for validating

the skill, e.g. team project assessment with oral

presentation.

3.3 Graphical User Interface

The Graphical User Interface (GUI) was developed

in such a way that it can be multi-lingual. The

current implementation supports the Greek and

English languages.

The GUI of the application first shows a login

screen. The user enters username and password and

then is shown a monitor. If the user’s role is that of

the administrator he has an extended list of possible

tasks. Most important are the tasks for inserting new

courses, for matching a course with a professor, for

inserting new verbs or generic skills. If the user’s

role is that of a tutor then the user can examine

his/her courses and select one for editing its outline

template using a web form.

courses

verbs

course

has verbs

levels

verb has

level

sentence

skills

course

has skills

acti vities

course has

acti vities

assessment

categories

validate skills

Figure 2: The ER Diagram. Rectangles represent Entity sets, diamonds represent Relationship sets and ovals represent

Attributes of entities or relationships. Trivial attributes such as entity names and keys are hidden. Bold connectors indicate

that at least one instance of a relationship exists, while if there is an arrow it means that exactly one instance of the

relationship exists for that entity. For example a course has one or more verbs, while a verb has exactly one level.

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Figure 3: The learning outcomes editor of the second section of the course outline form. The user can select the verb on the

left and then complete the sentence on the right. The user can see the verb’s level in the Bloom taxonomy in parenthesis.

Finally, the user can click on the left side (where the two arrows are shown) and drag and drop the outcome before or after

another. In the figure the user has used this feature to sort the outcomes based on the verb’s level in the Bloom taxonomy.

Figure 4: Documenting generic skills in the second section of the course outline form (the figure shows part of the form).

We will focus on the second and fourth parts of

the form, as these were identified earlier in sub-

section 2.2 as the most difficult parts of the course

outline template for the tutors.

Figure 3 shows the first part of the second

section of the course outline form that is about

entering learning outcomes. Note that the user does

not write verbs, he/she selects them from a drop

down menu. Thus, only qualified verbs can be used

for forming sentences. The text of the sentence is the

one recorded at the sentence attribute of the course

has verbs relationship at the bottom of Figure 2.

If a user indicates the need of a new verb, then it

can be inserted to the database by the administrator

using a specific form. That form also allows the verb

to be inserted in one or both of the supported

languages (English and Greek).

Note that we have introduced a feature that

allows the user to drag and drop a learning outcome

before or after another. This was inserted due the the

HQA requirement that only the six more important

ones should be considered for the HQA template.

Using our system, the user can write as many

outcomes as he/she wishes and at the end of the

process give priority to the most important ones.

Figure 4 shows a part of the list of generic skills

among which the tutor can select those that best

apply for the documented course.

Figure 5 introduces the fourth section of the

course outline form. At the start of the section the

user selects the lecture method (face to face or

distance learning), documents the use of ICT

technologies for teaching and, most importantly,

outlines the educational activities and the student

workload related to each one of them. The

application aids the user by automatically summing

up the workload and also indicating the needed

workload per unit of credit (ECTS). In this section

the tutor can also add more details in a free text box

(not shown in the figure).

Almost at the end of his/her work, the user

selects the method of assessment of the student’s

performance in the course. A relevant part of the

form is shown in Figure 6. The basic information

about all assessment methods is there, however, the

tutor can add more information in free text below

(not shown in the figure). The percentage of each

summative assessment method is added up to 100%.

If this is not the case a specific message informs the

tutor.

A Web Application for Aiding Tutors to Develop Course Outlines

327

Figure 5: The lecture method, use of information technologies and teaching organization/evaluation sub-sections of the

fourth section of the course outline form. The self study term shown in the form refers to the hours that the student will

spend to study at home.

Figure 6: The Students assessment sub-section of the

fourth section of the course outline form (the figure shows

part of the form).

The system guides the user by providing him

with available options in all the important fields of

the form. Numeric options, such as activity

workload, and student evaluation, are automatically

calculated for the assistance of the user and for time

efficiency.

Additionally, when filling in the form, window

notifications are displayed to avoid errors. Finally,

the instructor can export the data into a pdf file. Note

that the tutor doesn’t have to complete everything in

one session, whenever he/she wants to switch

context he can save his/her work and continue at

another time.

4 EVALUATION AND RESULTS

To evaluate our system we found volunteers among

the tutors of our university (from Lecturers to

Professors). 16 tutors completed the forms for 21

courses. Then they answered a short questionnaire to

help us in assessing their experience and the

performance of our system.

We had two types of answer, one denoting

agreement and another denoting satisfaction with a

range from 1 to 5 (1: strongly disagree/fully

dissatisfied, 5: strongly agree/extremely satisfied).

When questioning whether the system worked

properly and without failures, half of respondents

(50%) replied "Agree", 35.7% answered "Strongly

agree" and 14.3% remained neutral.

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In a subsequent question, most of them were

quite satisfied with the list of verbs given for the

recording of the learning outcomes, as the answers

prevailed to "Very Satisfied" and "Extremely

Satisfied", with rates of 64.3% and 35.7%

respectively.

Then, as far as the question about the list of

generic skills is concerned, the majority, 64.3%, said

it was "Extremely Satisfied", a smaller percentage of

21.4% believed it was "Very Satisfied" and the

remaining 14.3 % remained neutral.

The system automatically calculates the

semester workload based on individual activities

durations, and 64.3% of the tutors stated that this

feature helped them "Very much", 21.4% believe

that this calculation helped them and 14.3% were

indifferent.

In the question of the adequacy of the options

for student assessment, the largest percentage of

57.1% replied that they were "Very Satisfied",

while 35.7% were "Extremely Satisfied". 7.1 %

kept neutral.

The 64.3% of tutors found it "Very easy" to

become familiar with the system, 28.6% found it

"Quite" easy and 7.1% had a little more difficulty.

Overall, the 71.4% of the tutors who

participated were "Very Satisfied" with the use of

the system and 28.6% claimed they were

"Extremely Satisfied".

From the analysis conducted in the database of

our web application, the following observations

were drawn. The most popular verbs that were

chosen to record the learning outcomes of the

courses are presented in the Table 1. Each course

outline allows the user to select each verb once.

It is also interesting to focus on the Bloom’s

taxonomy level of the verbs employed by our 16

users. Looking at Figure 7 the reader can note that as

the levels rise more verbs are used.

Table 2 presents, in descending order, the

choices from the Generic Skills that the users

(tutors) claimed to be acquired by the students after

the completion of their courses. "Autonomous work"

has been chosen in 85.7% of the courses and

"Problem Solving" in 76.2% of the courses. The

"Decision-making" skill is also used frequently, in

more than 50% of the courses.

It is also notable that most of the tutors

disregarded the first Bloom taxonomy level and used

verbs from the second level up. In

Figure 8, it is

shown that most of the courses employ verbs from

the second to the fifth level of the taxonomy.

Table 1: Used verbs for documenting Learning Outcomes

for 21 courses. Sorted according to their popularity

showing the percentage of courses that used them.

Usage Verb (level)* Usage Verb (level)

57.14%

Recognise (2)* 19.05% Design (4)

42.86%

Use (3) 14.29% Select (6)

38.10%

Calculate (4)

14.29%

Assess (5)

38.10%

Analyse (4)

14.29%

Describe (2)

28.57%

Apply (3)

14.29%

Define (1)

28.57%

Develop (5)

9.52%

Design (5)

19.05%

Create (4)

9.52%

Construct (5)

19.05%

Distinguish (4)

9.52%

Revise (6)

*Verb level according to the Bloom taxonomy in

parenthesis

Table 2: Percentage of courses supporting specific generic

skills.

Courses Generic Skills

85.7%

Autonomous work

76.2%

Problem Solving

57.1%

Decision-making

47.6%

Time Management

47.6%

Computer Skill

42.9%

Research, analysis and synthesis of data

42.9%

Promoting free, creative and inductive thinking

42.9%

Numeracy

38.1%

Project design and Management

33.3%

Teamwork

33.3%

Written communication

Figure 7: Percentage of the available verbs used by the

tutors.

Figure 8: Percentage of the courses employing verbs from

the different Bloom taxonomy levels.

0% 20% 40% 60% 80% 100%

1. Knowledge

2. Comprehension

3. Application

4. Analysis

5. Synthesis

6. Evaluation

used %

unused %

0% 20% 40% 60% 80%

1. Knowledge

2. Comprehension

3. Application

4. Analysis

5. Synthesis

6. Evaluation

A Web Application for Aiding Tutors to Develop Course Outlines

329

5 CONCLUSIONS

We have presented a web application to support the

academic course outlining process in a student-

centered approach. Our aim was to aid the tutor in

outlining her/his courses, and our preliminary results

show that we are in the right track as our users were

satisfied with the developed system. However, as the

design of the database progressed we became aware

that more information could be later extracted from

the data. We presented some first results based on

the user acceptance trial.

According to the ABET guidelines (Felder &

Brent, 2003; ABET 2019-2020) for Engineering

Schools the curricula must be designed with specific

(although abstract) outcomes in mind (top-bottom

approach). Indicatively, the revised student

outcomes, which describe what engineering students

are expected to know and be able to do by the time

of graduation, in terms of knowledge, skills, and

behaviors, are outlined in Baccalaureate and in

Master’s level in ABET 2019-2020 criteria.

Based on our database, we can use a bottom-up

approach and discover abstract outcomes from the

specific ones. Thus, we can aggregate our findings

and find out what generic skills and general learning

outcomes are strengthened by a learning path.

There are multiple directions to follow now. One

is to establish this practice in our University and

extract more information about curricula,

departments and schools within it. This will be a

great decision support tool when redesigning the

curricula. Moreover, we can offer services, in the

form of a recommender system, to the students who

can plan their courses selection based on the skills

they want to enhance.

REFERENCES

ABET criteria for accrediting engineering programs 2019-

2020. https://www.abet.org/accreditation/accreditati on-

criteria/criteria-for-accrediting-engineering-progra ms-

2019-2020/#GC3 (access 2-1-2019).

Bagui, S., & Earp, R., 2004. Database design using entity-

relationship diagrams. Auerbach Publications.

Bennett, N., Dunne, E., & Carré, C. (2000). Skills

development in higher education and employment.

Buckingham, UK: The Society for Research into Higher

Education & Open University Press.

Bloom, B. S. (1956). Taxonomy of Educational Objectives,

Handbook I: The Cognitive Domain. New York: David

McKay Co. Inc.

Bradley, D., Nooman, P., Nugent, H., and Scales, B. (2008).

Review of Australian higher education. Canberra,

Australia: Department of Education, Employment and

Workplace Relations, Australian Government.

Chen, P. P. S., 1976. The entity-relationship model—toward

a unified view of data. ACM Transactions on Database

Systems (TODS), 1(1), 9-36.

Eurydice network. Greece, Quality Assurance in Higher

Education, https://eacea.ec.europa.eu/national-polici

es/eurydice/content/quality-assurance-higher-education-

27_en (access 28-12-2018).

Felder, R., Brent, R. (2003). Designing and Teaching

courses to satisfy the ABET criteria. Journal of

Engineering Education, vol. 92(1), pp. 7-25.

Ford, P., Goodyear, P., Heseltine, R., Lewis, R., Darby, J.,

Graves, J., Sartorius, P., Harwood, D., and King, T.

(1996). Managing change in Higher Education, Society

for Research into Higher Education & Open University

Press, Buckingham and Bristol.

Fullan, M. (1991). The new meaning of educational change,

Teachers College Press, New York, NY.

HQA (2016). Annual Report 2015. Athens, Greece, https://

www.adip.gr/data/HQA_report2015.pdf (in Greek).

Krassadaki, E. & Matsatsinis N. (2012). Redesigning

university courses based on generic skills via

multicriteria analysis methods. Int. J. Multicriteria

Decision Making, vol. 2 (2).

Krassadaki. E., & Matsatsinis N. (2017). Analysing and

measuring students’ experiences. 2017 IEEE Global

Engineering Education Conference (EDUCON), pp.

1326-1335.

Krassadaki, E., Doumpos, M., & Matsatsinis, N. (2017).

Teaching OR courses to satisfy educational and

professional needs in an Engineering School, in the

book J. Beliën et al. (eds.) Advances in Operations

Research Education, Lecture Notes in Logistics,

Springer.

Krassadaki, E., Lakiotaki, K., & Matsatsinis, N. (2014).

Students’ behaviour in peer assessment: a multi-criteria

clustering approach. European Journal of Engineering

Education, vol. 39 (3), pp. 233-246.

Leff, A., & Rayfield, J. T., 2001. Web-application

development using the model/view/controller design

pattern. In Enterprise Distributed Object Computing

Conference, 2001. EDOC'01. Proceedings. Fifth IEEE

International (pp. 118-127). IEEE.

National Committee of Inquiry into Higher Education

(1997). Higher education in the learning society

[Dearing report]. London: Her Majesty’s Stationery

Office.

Spanoudakis, N. I., Constantinou, E., Koumi, A. and Kakas,

A. C., 2017, June. Modeling Data Access Legislation

with Gorgias. In International Conference on Industrial,

Engineering and Other Applications of Applied

Intelligent Systems (pp. 317-327). Springer.

Spellings, M. (2006). A test of leadership: Charting the

future of U.S. higher education. Washington, DC: U.S.

Department of Education.

Teaching and Educational Development Institute (1996).

Bloom’s taxonomy of educational objectives, prepared

by Geoff Isaacs. The University of Queensland.

CSEDU 2019 - 11th International Conference on Computer Supported Education

330