Identifying Core Mobile Learning Faculty Competencies Based Integrated Approach : A Delphi Study

This study is based on the integrated approach as a concept framework to identify, categorize, and rank a key component of mobile learning core competencies for Egyptian faculty members in higher education. The field investigation framework used four rounds Delphi technique to determine the importance rate of each component of core competencies according to a consensus among the panelist experts. Out of 26 panelist participants, four core competencies findings emerged: (a) planning and designing, (b) assessment and evaluation, (c) technical support, and (d) teaching and learning. These competencies contained 90 specific key components distributed as 27 knowledge, 47 skills, and 16 attitudes.


Introduction
Rapidly progressing mobile technologies will be the lifelong platform of learning and the gateway to the knowledge age.The arguments around mobile learning (m-learning) are due to the one-dimensional outlook which focuses on "techno-centric" or "learner-centric" as an independent aspect to draw a concept framework of m-learning (Geddes, 2004;Sharples et al., 2007;Cheung & Hew, 2009;Taxter, 2009;Kissinger, 2012).Literature still classifying m-learning as informal learning, which is inconsistent with recent changes in mobile technologies such as protocols, operating systems and applications which provide students accessibility to deal with formal or informal educational systems according to learning contexts and their needs.This offers the opportunity of using m-learning as an important hybrid learning environment, by facilitating transition from formal to informal learning (Scheerns, 2009;Zhang et al., 2010).This trend is reaffirmed by some researchers considering that "the relationship between the context of learning and context of being" is unique to m-learning, which means that the learning process may occur in independent, formal, or socialized contexts (Frohberg et al., 2009, p. 313).Many forecasting studies showed the priorities of m-learning in higher education, which will play a big role in distance education of universities (Kurubacak, 2007;Hanganu, 2012).The growth rates of mobile phones in Africa and Middle East (AME) were the highest in the world (GSMA & Kearney, 2011).In the Middle East region, mobile penetration rates were expected to reach 125.5 % in 2015 (Cherrayil, 2010).Nearly half of college students worldwide got smart phones, most of them are inclined to use mobile devices for academic purposes (Alexander, 2011).In spite of the educational need and growth of m-learning technologies, the number of researches connected to theoretical and pedagogical aspects of m-learning still limited.This caused a lack of sustainable integration into formal educational contexts and the way to support and develop faculty skills when using m-learning (Cochrane, 2012;Peng, Su, Chou, & Tsai, 2009;Ekanayake & Wishart, 2014;Baran, 2014).Few studies and projects conducted to development faculty skills on m-learning system revealed the need for distinction between m-learning and mobile usage, as well as the necessity for exploring the pedagogical potentials of mobile technologies (Schuck et al., 2013;Bates & Martin, 2013).Yet, in AME region no systematic researches have been conducted on identifying m-learning competencies for faculty members in higher education, due to the lack of awareness among them and administrators about the add values from m-learning and the viability of Wireless/ handheld devices in the online program (Luvai, 2007;Altameem, 2011;Isaacs, 2012).
The current study aims to produce a list of core m-learning competencies for faculty members in higher education based on integrated approach.Most of the previous studies produced a list of competencies conducted with distance learning or web based learning as a formal learning environment for faculty members in higher education (Williams, 2000;Abdulla, 2004;Bailie, 2011).In addition the behavioral approach of the concept framework of identification competencies in the majority of previous studies considered these competencies as a set of skills and knowledge (Palloff & Pratt, 2003).This means a competency concept "sub-set of itself" (Deist & Winterton, 2005, p. 29).However the identification competency based the integrated approach (KSA approach) (Note 1); considered it as a complex combination of knowledge, attitudes, skills, and values displayed in the context of task performance (Kerka, 1998).The reasons behind that is identifying m-learning competencies to fill the need for coherence between technological and pedagogical aspects of mobile learning; field practices reflected positive changes in direction and attitudes among faculty members and students about using m-learning in higher education.Design m-learning competencies list according to this approach represented as a benchmarks for tracking the quality of m-learning system through indictors, describe what faculty should be known, do and aware when using these kind of learning environment .Few studies proposed models of how the competencies woven into integration by synthesis competencies lists as a sequence of what should online instructors doing before, during and/or after the course (Smith, 2005).The add values from using this approach fill the gap of m-learning training program directed by faculty competency in higher education.The list of m-learning competencies represent guidelines for policies and decision making for supporting using it in higher education of Egypt.This is the first study to use integrated approach as a concept framework of design a list of key components of core faculty competencies relevant to m-learning as a hybrid learning environments in higher education.

Mobile Learning Conceptualizations
Mobile devices occupy a significant part of our nowadays life (Pettit & Kukulska-Hulme, 2007).The tablet technology offers a wide variety of applications that have the potential to enrich the learning experience (Hamshire & Crumbleholme, 2012).Some researchers pointed a lack of a standardization in the term and suitable contents, methods and assessment activities of m-learning, so it still immature as a term of educational technology domain (Pea & Maldonado, 2006;Taxler, 2007).Literature classify m-learning definitions into two main sets, the first one focused into technological aspect which consider it as a form of existing distance learning (d-learning), electronic learning (e-learning), and learning situation Practices without limits of affixed location (Gergiev et al., 2004;Naismith et al., 2004;Geddes, 2004).Second set of definition moved away from "techno centric" and went back to the learners, contexts and the unique mobile practices in education as a way to make deep understanding authentic learning, learner-centric and contexts of experiences (Sharples et al., 2007;Cheung & Hew, 2009;taxter, 2009;Kissinger, 2012).Other researchers tried to categorize the perspectives of m-learning domain as Winter (2006) who summarized four main perspectives of m-learning: (a) techno centric which m-learning is primarily seen as learning supported by mobile devices, and the focus is on the technology; (b) m-learning is seen as an extension or a subset of e-learning, and m-learning research is primarily part of e-learning research; (c) mobile devices which are uses for just to complement and augment formal education; and (d) m-learning ( student-centered) it is about mobility and context.Moreover Luvai and Motiwalla (2007) suggested framework integrated the ideas of mobile technology and e-learning into m-learning environments based on active content delivery, personalized, collaborative, constructive and conversational learning models.As a guide line about faculty roles in m-learning systems Roschelle and Pea (2002) suggested that wireless internet learning devices could be uses for computer supported collaborative learning where the teacher becomes a guide or coach and learners take the initiative in their learning.Furthermore, wireless devices are tools make faculty flexible for extending the learning process beyond the classrooms and homes to the remote places like airports or trains as informal learning environments (Virvou & Alepis, 2005;Khaddage & Lattemann, 2013).Design principles of m-learning promote engagement and self-directed learning and staff plays the role of facilitator, provide an environment to integrate all learning activities assess formatively, support the notion of seamless learning (Zhang et al., 2010).The main features of m-learning are in supporting learning object management system (LOMS); which allow instructor, student and experts participate collaboratively in the cycle of design, development, sharing, editing, reusing and evaluation of learning object as a form of lessen or courses activities.Some researchers indicated that m-learning materials should use two types of advance organizers, the expository advance organizers to allow learners to store the general framework; and comparative advance organizers to allow them to use existing knowledge to make sense of and take in the new materials (Ausubel, 1974;Ally, 2004a).With the same context, the learner control of learning situation is the heart of instructional design of m-learning system which should contain intelligent agents to determine what the learner did in the past and adapt the interface for future interaction with the learning materials; a course or lesson will comprise a number of learning objects which are sequenced to form an instructional event for a lesson or learning session (Ally, 2004b;McGreal, 2004;Lai, Khaddage, & Knezek, 2013).Beside that m-learning, help learners to be independent and increase self-motivation (Che et al., 2009).Also Valk, Rashid and Elder (2010) referred to the benefits from m-learning in development of educational processes and introducing effective teaching methods based learning theories.Additionally, Hargis et al. (2013) showed the views of faculty members who received training on iPads and found that iPads supported student-centered teaching.

Competency Identification Based Integrated Approach
Some researchers described competency as a "fuzzy concept" (Arnaud & Lauriol, 2002, p. 12).Boak (1991) argues that "competency" in the American sense complements 'competence' as uses in the UK occupational standards.Other researchers pointed what should be considered to define a competency like Cheng and hung ( 2004) who refer to several aspects when define competency, for example performance of work or anything specified independently to achieve a certain goal, determine skills, knowledge and motivation to achieve the goal as a basic components of competencies.Literature have focused on three main approaches identifying competency, the behavioral, functional and multi-dimensional or integrated approach which called KSA approach (Weinert, 2001).The integrated approach considers competency as a complex combination of knowledge, attitudes, skills, and values displayed in the context of task performance (Kerka, 1998).Deist and Winterton (2005) explained a typology of competency according to integrated approach to include four aspects as follow: a) conceptual which included cognitive, knowledge and understanding; b) operational aspect as functional, psycho-motor and applied skill; c) attitudes; d) meta competency which concerned with facilitating the acquisition of the other substantive issues.The benefits from organize the list of m-learning competencies based on this approach transit further upgrade of this list from just delete and add components separately according recent changes in m-learning domain, to systemic upgrade based on the relative relationship between these components.
A research trend of identification mobile learning competency based integrated approach provides opportunity to face the lack of integration between pedagogical and technological aspects of mobile learning.Bailie (2006) recommended that further study of how faculty competency is influenced by the changes in technology is strongly encouraged, also "a follow-up" study should be completed at 5-and 10-year intervals to consider whether the identified competency list has changed as a result of advancements in pedagogical approach, practitioner and consumer interests, and online staff development initiatives.Varvel (2007) suggested that technologies, incoming faculty, student needs, and curriculum are always changing, so as the competencies should be updated.Most of previous studies produced (e-learning) or online competencies lists for faculty members in higher education based on behavioral approach which constructed and design it as a sorting list by using different ways as Delphi techniques to define, categorize and ranked these competencies according perceptions of experts, online university faculty and students (Williams, 2000;Abdulla, 2004;Shank, 2004;lee & Hirumi, 2004;Bailie, 2011).The notion behind using integrated approach to identify mobile learning core competencies list is to emerge it into coherent design by determine experts opinions consensus for each key components (KSA) of core competency and combine it according to importance rate through a series of investigations based on Delphi techniques.

Participants
Current study was conducted during 2013-2014 academic year.Selecting study sample required surveying the online instruction experts CVs which posted on websites and official social networking at universities of Egypt and Middle East region.The general criteria of selecting appropriate participants as the panelist experts are as follow: (a) obtained a doctorate degree and have experience at least 3 years of work in the field of e-learning system; (b) has experiences and activities of working with formal or informal e-learning environments; (c) worked as staff in departments of education technology in education colleges, software engineering in computer science colleges, and deanships of e-Learning , d-learning and community services in higher education; (d) knowledge and skills of design and delivery learning material via mobile applications .Fifty-seven experts have been selected according to these criteria, and only 26 experts were responding positively to the researcher e-mail invitation for participation as panelist experts of the current investigation framework.

Methods
In the case of studies that focus on identifying competencies, the Delphi technique is uses to clarify, update established competency lists to support related future development (Egan & Akdere, 2005).It is used for forecasting and issue identification, prioritization based on social judgment analysis (Okoli & Pawlowski, 2004).The Delphi technique, mainly developed by Dalkey and Helmer (1963) at Rand Corporation in the 1950s, it was widely accepted method for achieving convergence of opinion concerning real-world knowledge solicited from experts with certain topic areas.The notion of Delphi technique "two heads are better than one, or…n heads are better than one" (Dalkey, 1972, p. 19).As noted by Helmer (1994), a Delphi study is a reliable method for investigating the formation of a group judgment, the exploration of ideas, and the production of suitable information for decision making.Furthermore, this technique provides survey tools for facilitating consensus among experts who had special knowledge to share, but who were not always in contact with each other (Adler & Ziglio, 1996).Common surveys try to identify "What is" where the Delphi technique attempts to address "What could/should be" (Miller, 2006).There was little agreement about the size of panelist experts in the Delphi studies (keeney et al., 2001).Most of researchers recommend 10-18 experts on a Delphi panel, and some studies indeed uses panels that fall with this range (Okoli & Pawlowski, 2004).Action management frameworks when we using Delphi technique based on two methods, The first one is brainstorming through informal meeting, where panel of expert responded to inductive and deductive open-ended questions (McGuire & Cseh, 2006).The second methods asked participants to respond individually to a specific content in a structured of close end questionnaire (Rossouw, Hacker, & Devries, 2011).Information and Communications technologies (ICT) provides facilities and save time in all Delphi processes specifically in designing and distributed survey tools among participants, collect responses or feedback and storage data.Some researchers suggested modified Delphi technique, the main features of it in the first round which begins with panelists being offered a set of predetermined items from various sources including the findings of previous studies, reviews of contemporary literature, or interviews with content experts, also the statistic model or formulation to identify and ranking competencies (Bailie, 2011).Therefore, the action framework of Delphi technique in the current research showed in Table 1.The first round targeted production initial list of competencies by designing it as an open-end questionnaire include items represented suggested competencies and key component (KSA) based on reviewed literature which related to the characteristics and attributes of m-learning environments, also conducted studies which determined a list of faculty competencies in e-learning and d-learning as references guides, after that we asked participants individually to clarify and add competency statements and key components which related to each competency during virtual brainstorming meetings.In the second round we collect all panelist experts responses which appears in the first round and prepare a closed-end questionnaire included all proposed items and uses a five-point Likert scale (1 = very important, …, 5 = very unimportant) to rate experts perceptions for each competency.We write off competency statement which does not included (KSA) or only has one component because that is not compatible with competency concept integrated approach.To raise the outcomes from Delphi technique we estimated validity and reliability of close-end questionnaire as a measure tools of Delphi techniques, by Appling it with a pilot sample of (6) experts to determine validity according to Cronbach coefficient.Validity coefficient was (0.731) which is acceptable for using questionnaires as measuring tools.Internal consistency reliability of questionnaire determined by Kudser-Richardson equation, estimated value founded (0.752).Internal consistency reliability of questionnaire which determined by using Kudser-Richardson equations showed estimated value (0.752) which mean acceptance reliability level.In round three we calculate mean score for each item based on individual responses of panelist experts.In round four criteria of considering competency as a core one based on rated point 1 or 2 of at likart scale by at least 90% of participants'.The combination between key components in one list for each competency based on panelist experts consensus.Categorizing, and ranking these key components required two processes as followed: (1) make a code for each component referred to its type and number on measuring instruments, (2) determined important rate for each component and placed it in the final list according the value of mean score.Rates each competency in close -end questionnaires using a five -point Likert scale.

Round/no Manager Actions Experts actions
3 Calculates mean score and percentages, and distribution of the panelist experts' responses for each key component of competencies.
Reviewed individual rating of each component in view of group response.

4
Categorize competencies which rated point 1or 2 at likert scale by at least 90% of panelist experts as a core competencies.
Reviews the combination between key components of each core competencies based mean score.

Results and Discussion
In the Delphi technique, outcomes of investigation panelist experts' consensus included qualitative and quantitative data.Table 2 showed the results of the final round of Delphi technique which presented 4 core competencies ranked according to the responses percentages of panelist experts.These competencies consisted of 90 specific key components included 27 knowledge, 47 skills, and 16 attitudes components.As shown in Table 3, the results of rated importance of planning and designing competency key components according to panelist experts responses revealed that faculty should be have a clear knowledge and skills about designing feedback and helps via mobile learning environments as a priorities needs which reaffirmed the Bailie (2011) sequel investigation that considered feedback skills in the top ranking of effective Online Instructional competencies as perceived by online university faculty and students.There were consistency between the consensus of panelist experts, and the previous literature about strengthening the roles of the faculty members in learning object managements system (LOMS) as a learning system appropriate with the features of m-learning and facilitate learner control of learning object as a heart of instructional design of m-learning system (Ally, 2004a;Ally, 2004b;McGreal, 2004;Khaddage & Lattemann, 2013).Faculty should be willing to explore new trends of design m-learning apps and focuses on designs of social learning activities via mobile technologies represent important attitudes components.Note.1=Very important, 2=Important, 3=Neutral.
Code number: placement of key component at measuring instruments.
Figure 2 pointed the percentages distribution of the panelist experts responses for each component of evolution and assessment competency.41.9% of the responses referred to the attitude component as a very important component, 22.6% as important, and (19.4%) were neutral.However, 35.1% of the responses indicated that the skills component was very important, and 57.2% indicated it as important.For knowledge component, these figures were 39% and 61%, respectively.As shown in Table 5, importance rate according to panelist experts views related technical supporting competency components indicated that faculty should be mastery follow these skills: a) perform technical issues for manipulated with formal and informal learning system via smartphone; b) using mobile operating systems.Also importance rate indicated the ethical aspects of using mobile in learning process represented in the component respect technical issue which related to privacy of student data.Understanding technical issue as requirement to use m-learning as learning objects management system or open learning resources is a very important knowledge component.The convergence between a number of key components, specifically knowledge and skills components in technical supporting competency confirmed views that penetration of mobile technology to higher education of AME still the early stages (Altameem, 2011).Note.1=Very important, 2=Important, 3=Neutral.
Code number: placement of key component at measuring instruments.Although the above lists of core competencies may seem complex and largely duplicates the information, it corresponds with Kerka notation "integrated approach [should recognize] levels of competence-entry/novice, experienced, specialist-rather than a once for all attainment.Interpreted broadly, competence is not trained behavior but thoughtful capabilities and a developmental process" (Kerka, 1998, p. 6).

Conclusion
Identification m-learning faculty competencies based on integrated approach represent a new trend of recent researches on this domain that cross the limits of identify competencies as a sorting list to interactive list designed according to the combination between the knowledge, skills and attitudes as components of each competency.Current research is trying to fill the gap of faculty needs of what faculty members should be able to know, do and aware when employment m-learning as a formal or informal learning environment in higher education based on consensus of experts perception, which also so importance as a guide line for policies and decision making of supporting using m-learning in higher education of Egypt.Identification of key components of m-learning core competencies confirmed a unique pedagogical and technological characteristics of m-learning different from the rest of the other (e-learning) environments, which pointed the needs to do further comparative studies between m-learning environment and other (e-learning) environments to determine a difference in the roles and tasks of the faculty members in these environments.Also researcher suggests doing a sequel study to identify m-learning competencies as perceived by faculty and students in higher education.As well as we recommended developments training programs directed to acquisition of m-learning competencies for faculty members in higher education.

Figure 1
Figure1showed the total percentages of the panelist experts responses at 5 point likert scale for each components of planning and designing competency.53.8% of responses indicated that knowledge components are very important, and 46.2% of responses referred to it as an important component.The corresponding figures for skills components were 42.9% and 51.1%, respectively, with 5.5% of the responses were neutral.Percentage of responses which related to attitudes components referred to 32.7% as very important, 61.5% as important, 5.8% as neutral component.

Figure 1 .
Figure 1.Distribution percentages of planning and design competency key components

Figure 2 .
Figure 2. Distribution percentages importance of evolution and assessment competency key components

Figure 3 .
Figure 3. Percentages distribution of technical supporting competency key components

Figure 4
Figure 4 pointed to the percentages distribution of the panelist experts responses for each components of teaching and learning competency.A response percentages related to a component which represented attitudes referred to 43.8% of experts panel found it as a very impotent component, 38.5% is important, 17.7% is neutral.However, 51% of responses considered the skills components a very important, 38.1% important.Knowledge components represented 46.7% of the responses as very important, and 49.5% as important components.

Figure 4 .
Figure 4. Percentages distribution of teaching and learning competency key components

Table 1 .
The action framework of delphi technique

Table 2 .
Descriptive statistics of core mobile learning faculty competencies key components

Table 3 .
Importance rate of planning and designing competency key components

Table 4 .
Importance rate of assessment and evaluation competency key components

Table 5 .
Importance rate of technical supporting competency componentsFigure3pointed to the percentages distribution of the panelist experts responses for each component of technical supporting competency.46.6% of responses rated attitudes components as very important, 47.6% as an important, and 5.8% as neutral.Percentages related to the skills components indicated that 60.1% of the responses found these components very important, 39.2% important and 0.7% neither important nor unimportant.As well as knowledge components concern, 52.2% of the responses indicated them as very important, 43.4% as important, and 4.4% as neutral.

Table 6 .
Importance rate of teaching and learning competency components