Formato para evaluar el macro entorno

This thesis tackles the design of a potential pedagogical m-learning framework and the development of a proactive (i.e. automatically without input required from users) approach for retrieving users’ learning contexts without the use of context-aware sensor technologies. The user’s learning contexts are taken into consideration, as well as the learner’s current situation and/or location. The suggestion mechanism framework makes recommendations for possible appropriate learning/studying materials for students, enabling them to perform under their current circumstances and location.

The purpose of this proactive approach is to reduce the number of interactions that users may be required to enter into the mobile device to inform about their current situation, whilst ‘on the move’. The target users of this framework are university students. In particular, I wish to examine an appropriate set of suggestion rules for the Java programming language subject to be incorporated into this framework. This is so that students can have appropriate Java materials suggested to

them based on their current learning contexts. The aim is to potentially enhance their learning experiences and increase their learning effectiveness, whilst learning Java ‘on the move’. I envisage that careful consideration of which Java materials are appropriate for which situations, and recommending only those appropriate materials to learners for particular situations, can be beneficial for students in terms of their learning/studying. This argument is supported by Martin and Carro (2009), Cui and Bull (2005), and Beckinget al. (2004) among others.

I decided to incorporate Java LOs from existing online repositories for use within my framework because there are a large number of existing high-quality reusable LOs available. I also conducted an exercise to locate available high-quality Java LOs, which can be feasibly incorporated into my framework (see chapter 8).

To help me examine these issues, I constructed a theoretical framework from an extensive literature review. Subsequently, I conducted two feasibility studies, an interview and diary study, relating to the framework to analyse their real potential, in terms of two perspectives – pedagogical and usability. Then I conducted two

framework validation studies, a Java LOs experiment and an exercise to locate available high-quality LOs. Finally, I conducted a technological feasibility study in

order to determine whether this framework can be potentially developed and implemented with the required components.

My research was conducted from an interdisciplinary approach, combining computer science and education. The aim was to bring together the three important design fundamentals (pedagogical, usability and technological) to form a well- designed pedagogical m-learning framework. The pedagogical and usability studies have helped us to determine a) the significant learning contexts that should be deployed within our framework, and b) a set of suggestion rules for recommending

appropriate Java learning materials for different situations. The first validation study helped to gain user feedback on my framework about the appropriateness of the recommended Java learning materials for different situations as well as other resulting enhanced learning experiences or benefits and so on. The second validation study has helped me to visualise the potential number of Java LOs that can be deployed within the framework in order for a larger set of materials to be made available to learners. The refined requirements established via these studies are a contribution to the technological design and potential implementation of my framework, as presented in chapter 9.

The thesis was not focused on the technological use of mobile devices or an implementation of a mobile software application, but rather the pedagogical and usability design issues of a technologically-feasible m-learning framework. The two validation studies have helped to prove the realistic deployment thereof.

Chapter two presents a review of the literature on m-learning and describes it from the perspective of four succeeding generations – ‘non-adaptive’, ‘learning-

preferences’-based adaptive, ‘learning contexts’-based adaptive and ‘learning-

contexts’-aware adaptive. I distinguish and highlight the differences between these

generations and provide related applications within these generations to illustrate the respective characteristics. The initiation of a ‘context’ concept is explored and

subsequently a ‘learning context’ is derived for describing contexts with pedagogical

attributes. I identify and analyse challenges associated with learning contexts including difficulties in retrieving them. Current context-aware m-learning research primarily focuses on the technological and usability perspectives; there is a lack of studies which focus on the pedagogical aspect. I have further classified the applications of the latter ‘learning-contexts’-aware adaptive generation into three

different types of learning applications -context-aware location independent learning

applications, context-aware location dependent learning applications and context-

aware situated learning applications. The chapter concludes with a range of

methodologies and approaches which can be adopted for the evaluation of m-learning applications. Each of these approaches focuses on the evaluation of one of the three following aspects -pedagogical, usabilityandtechnological. Furthermore, difficulties

and challenges of evaluating m-learning applications are described.

Chapter three explains the research methodology I adopted to tackle the design of a proactive context-aware m-learning framework which acts as a suggestion mechanism to recommend appropriate materials to students in different situations. Central to the thesis is the derivation of a theoretical framework based on an extensive literature review and research findings – called mCALS (mobile context-aware

learning schedule) framework. The design of this framework comprises the use of the student’s learning schedule (i.e. electronic diary) integrated in the mobile device to retrieve their location and available time contexts. The process of the framework derivation forms the first section of this chapter and is the first phase of the research methodology. To examine the potential feasibility of the framework, the methodology adopted includes a pedagogical, usability, technological and two validation studies.

Our chosen research methodologies are influenced by the difficulties and challenges in evaluating m-learning, as described in 2.8. The rationales for conducting these studies are described in the subsequent sections of this chapter. The pedagogical

study uses an interview methodology to ascertain from the qualitative perspective and the usability study consists of a diary study to determine from the quantitative

perspective the following three aspects - 1) The potential deployment of a learning schedule for retrieving learning contexts; 2) The significance of the proposed learning

contexts to be deployed within a context-aware suggestion mechanism; 3) A set of suggestion rules to recommend appropriate Java learning materials to learners studying in different circumstances. Subsequently, the procedures in which I conducted the two validation studies are described in detail. Finally, thetechnological

study consists of a technical framework design to illustrate an implementation of whether it is technically feasible at the present time. The final requirements of the framework are elicited from the data analyses of the pedagogical and usability studies to form the final technical framework design. The validity and reliability of these research methodologies, together with the data collection and analysis methods are explained in the relevant sections of this chapter.

Chapter four illustrates the derivation of the theoretical mCALS framework. The intended functions of this framework are demonstrated with a set of scenarios concerning four different Java-learning students. The proposed contributions resulting from this framework are discussed in the context of related works. Five research questions are addressed in this chapter, from a theoretical perspective.

4A: Can a proactive approach for the retrieval of learning contexts without

the use of sensor technologies be incorporated into a suggestion mechanism?

4B: Which learning contexts are significant in the recommendation of

appropriate learning materials?

4C: Which types of learning materials are appropriate for recommendation to

students under different circumstances?

4D: What are the design modules of the framework?

4E: What are the user requirements of the framework?

Chapter five presents the data analysis relating to the potential adoption of a learning schedule for retrieving learning contexts. This data analysis is derived from

both the interview and diary studies. Three main research questions are addressed in this chapter, from the qualitative and quantitative perspectives respectively.

5A: How feasible is the adoption of a learning schedule for retrieving learning

contexts from aqualitativeperspective?

5B: How feasible is the adoption of a learning schedule for retrieving learning

contexts from aquantitativeperspective?

 Can users plan their schedule ahead, conform to it and keep it up-to- date?

 Can the location and available time be accurately retrieved from the learner’s diary?

5C: How do participants view the use of mobile devices as a learning tool?

Chapter six presents the data analysis relating to a) the significance of the proposed learning contexts (in chapter 4) to be used within a context-aware suggestion mechanism, and b) the possible recommendations of appropriate learning materials for different circumstances, i.e. a set of suggestion rules. The data obtained from the interview and diary studies is analysed and presented from the qualitative and quantitative perspectives respectively. We also describe the refined user requirements of the framework, based on these results. Four research questions are addressed in this chapter. Significance is in terms of how much the learning is affected.

6A: How significant are the proposed learning contexts, which are to be used

within a context-aware suggestion mechanism, from aqualitativeperspective? 6B: How significant are the proposed learning contexts, which are to be used

6C: Can a set of suggestion rules be derived for recommending appropriate

Java learning materials to students based on their situation?

6D: What are the refined user requirements of the framework?

I conducted data triangulation of the study results of chapters five and six in order to strengthen the integrity of my results. The data triangulation is presented in 3.7.

Chapter seven presents the data analyses of the first validation study of the framework. I constructed a suggestion mechanism which students can access online from any computer machine. At the beginning of the learning session, students are asked to choose their current motivation level, their available time and their Java proficiency level. A number of LOs which are thought to be appropriate for students situated within these contexts are presented and the student may choose one to learn/study with. After the student has completed the learning object, they are asked to complete a questionnaire/feedback form to provide their opinions about their learning experiences. Two main research questions are addressed in this chapter, as follows:

7A: Is the proposed set of suggestion rules appropriate for use within my

context-based suggestion mechanism framework?

 How useful had students found the study of learning objects in the proposed contexts?

 Were their learning experiences of the LOs more enjoyable as a result of studying the objects in the proposed learning contexts?

 How appropriate were the suggestion rules for recommending Java LOs to students?

Chapter eight presents the data analyses of the second validation study of my framework. In this chapter, I investigate the possibility of integrating a larger quantity of high-quality and reusable LOs into the framework. One research question is addressed in this chapter.

8A: Which Java LOs in the public domain are high-quality and reusable and

can be incorporated into the framework?

The refined framework and final requirements are illustrated in chapter nine. A software engineering design approach is adopted to demonstrate the technical feasibility of the framework using current mobile and context-aware technologies. Six research questions are addressed, from a technical perspective.

9A: Can the proactive learning contexts retrieval approach be implemented?

9B: Can the framework be strengthened?

9C: Can users’ learning contexts be incorporated into the framework design?

9D: How can m-LOs be incorporated into the framework design?

9E: Can a set of suggestion rules be incorporated?

9F: What are the system architecture and configuration of the final framework?

In chapter ten, I conclude the thesis with recommendations for future work. Then my research contributions and a discussion summarising how the research questions are addressed in the thesis are presented. Finally, limitations of the research work are discussed.