Señales transmitidas por la VTU-O .1 O-P-TRAINING 1

There are many factors highlighted in studies that limit the effectiveness of blended learning, which have created scepticism from academic researchers over many years, whom are still not convinced on its effectiveness as an educational

this, many studies have established that the obstacles to blended learning are: issues of learner access to resources, learner motivation to use additional online learning tools, producing meaningful and beneficial integration of online learning tools into the course, and the reliance on the learner’s prior IT training and competency (Dearnley, et al., 2006; Dantas & Kemm, 2008; Wormald, et al., 2011; Kobayashi & Little, 2011).

Social issues also play an extrinsic but significant component in the uptake/suitability of blended learning in certain groups i.e. non-traditional students, who are described as: ‘being from an ethnic minority group; having a long-term disability; possessing non-standard qualifications on access to higher education; being aged over 25 years on entry to university; or being from lower socio-economic groups of origin,’ (Holley & Oliver, 2010). Since the advent of education for all in the 1960s, Higher education access has shifted from being a privilege to a right (Schuetze & Slowey, 2002). There is record highs of enrolment of UK domiciled students for example, 2,087,615 in the academic year 2009/10 in to higher education institutes published by Higher Education Statistics Agency (2011). However, actual participation in these institutes can be limited by learner educational backgrounds, age; and economic barriers, which require them to work full or part-time (Holley & Oliver, 2010). In turn, this affects the time available to study, even with blended options. A Department for Education and Employment survey with 1,418 responses (46 of which were from academics) carried out at the University of Northumbria found that 40 % of full-time students in employment during term time believed that employment ‘had a deleterious effect on their

academic performance,’ which increased to more than 50 % for students working more than 12 hours per week (Little, 2002).

Holley & Oliver (2010) state that of the students they interviewed two thirds were mature students, or those for whom English is not their first language or who experienced financial hardships, and reported any or all of these factors can affect their performance. In addition, many instructors doubted their learner’s confidence, autonomy and aptitude to learn independently. Moreover, this places blended learning and Padilla-Meléndez’s, et al. (2008) popular notion of learners being ‘digital natives’ in doubt as when under scrutiny has been found not to be the case as learners are not the ‘prolific users of technology’ they are perceived to be (Holley & Oliver, 2010).

In addition, factors such as learner and instructor preference, the hindrance of learner mind-set: learners who prefer or expect traditional teaching methods are found to affect the effective use and delivery of blended learning (Dearnley et al., 206; Holley & Oliver, 2010). The Department for Education and Skills (2002) found that 67% of 16 year olds expected part of their learning and teaching to incorporate e-learning as they had regularly used these tools in and out of classes, but what of the older learners, who fall within the homogenised description of non-traditional students? Dearnley et al. (2006) found that women were more reluctant to use technology than men. Although women are no longer categorised as non-traditional students, in the majority of ethnic groups (as they account for just more than 56% of all higher education institutes student participation) a

reluctance to use technology would be a serious problem in blended learning courses (Table 2.2).

Table 2.2 Students in 2009/10 by mode, level and gender (HESAb, 2011) Gender/Mode Undergraduate Postgraduate Total

Full-time Female 737,125 146,980 884,105 Full-time Male 596,775 151,275 748,050 Full-time Total 1,333,900 298,255 1,632,155 Part-time Female 364,740 163,340 528,080 Part-time Male 216,070 117,105 333,175 Part-time Total 580,810 280,450 861,260 Total Female 1,101,865 310,320 1,412,185 Total Male 812,845 268,380 1,081,225 Total 1,914,710 578,705 2,493,415

Meßmer and Schmitz conducted a study in Germany comparing computer literacy and gender (Meßmer & Schmitz, 2004). They stated that differences in competency were only noticed between genders as a ‘generation problem’. There was only a 2% difference in internet usage between male and female teenagers; this difference increased to 18% with age for those aged between 50 to 60 years old. There was also an inverse relationship between education and gender internet usage: the lower the education the higher the gender differences between males and females without vocational training, whereas males and females with postgraduate training differed minutely in computer literacy. These finding were reflected in Ikolo & Okiy’s (2012) study on gender differences and computer literacy in medical students, they identified gender difference in the number of hours students spend with a computer weekly (highest responses 28 (56%) males

11-15 hours, highest response 19 (52%) females 1-5 hours). However, Meßmer and Schmitz stressed that this should not engender a difference between females and males as competencies varied considerably depending on the course. Sometimes females were found to have more similarity with their male peers in for instance, computer sciences, as opposed to archaeology degrees.

Meßmer & Schmitz (2004) also suggested that creating a ‘modular system’ within the virtual learning environments could remove technical barriers, whereby only the tools required for tasks are available, thus making it intuitive and easy to use and providing an opportunity to deliver a personalised learning environment. This presents an opportunity for educators to adapt our pedagogic approaches with the technological tools in the virtual learning environments to learning and support the traditional teacher/student roles to create individualised pathways to suit their individual needs and interests (Attwell, 2007; Dabbagh & Kitsantas, 2012; Johnson & Brierley, 2007; Schaffert & Hilzensauer, 2008). Personalised learning environments encourage learners to participate and engage by providing learners with a variety of tools to facilitate coordination of different learning contexts (Attwell, 2007; Schaffert & Hilzensauer, 2008).

The successful integration and utilization of blended learning is not the sole responsibility of the learners, but also the educational instructors alike. A study into web-based learning at four higher education institutes in South and West England found that lecturers and tutors could also experience ‘technophobia’ and ‘technological illiteracy’ (Salmon & Jones, 2004; Torrisi-Steele & Drew, The

understanding of academic blended practice, 2013). The same article observed all academic staff, who participated encountered problems in ‘translating teaching materials …into collaboratively produced WBL’ and had issues with the aspect of time: with regard to preparing web-based learning (WBL) resources, becoming acquainted with the software, and the lack of physical support and recognition of instructors’ increased workload and accomplishments. Simultaneously, ‘managers were confused about whether or not there were funds to ‘buy-out’ staff time’ (Salmon & Jones, 2004). Instructors expressed the need for clearer objectives, established roles and responsibilities, technical support for specialist advice as well as project deadlines. This was believed to move toward less autonomy, more collaboration through sharing of knowledge, skills and practices within higher education institutes and across them to help maintain academic excellence and innovative teaching and learning methods.

Torrisi-Steel and Drew (2013) also indicate that research into understanding the problem with academics adoption of effective blended learning that may affect widespread uptake of the practice in higher education.

In summary, the most overwhelming obstacle to blended learning is learner capability as Holley and Oliver (2010) have demonstrated in their study and the shifting locus of control from the teacher to the learner (Littlejohn & Pegler, 2006). Learners who come from lower socioeconomic groups, with low educational qualifications are most likely to suffer and not successfully learn and complete the tasks provided on Online Learning tools; at which more confident and independent

learners would excel. Therefore, requiring instructors to recognise those learners, who can work online independently, and those requiring greater support and guidance is critical to their success (Littlejohn & Pegler, 2006). As such the limitations of blended learning encompass the structural, operational and social aspects of learning environments, but they could be overcome with forward planning, collaborations, investment in time and money to ensure that an effective learning system is designed and maintained.