Personalized learning
Personalized learning through use of ICTS
Tyler Reid, Memorial University of Newfoundland
Problem
Learners’ needs and classrooms are becoming increasingly diverse across North America and around the world (Howery, McClellan, & Pedersen-Bayus, 2013). As a result, “instruction needs to be specialized to meet the needs of each learner” (Howery et al., 2013, p. 294). Teachers are facing resistance from 21st century students who are not satisfied being passive recipients of static knowledge; conversely, they are seeking greater involvement related to decision making in a dynamic and participatory learning environment (Jones & McLean, 2012). Despite student demands, many universities still rely on traditional lectures or learning management systems that do not allow learners’ to set personal goals and connect with peers (Dabbagh & Kitsantas, 2012). This type of linear learning contradicts with knowledge about how students actually learn (Hurson & Sedigh, 2010). Furthermore, many standardized distance courses limit and restrict personal creativity and empowerment (Bidarra & Araujo, 2013). Creating a PLE in a face-to-face environment is challenging because many teachers are unprepared to deal with diverse learning needs (Jones & McLean, 2012). Additionally, traditional classrooms are limited by space and time which leads to instructors simply covering the core content (Abik & Ajhoun, 2009). Finally, when instructors use a “one-size-fits-all” approach to student assessment, many learners never feel successful because they are constantly compared to their peers (Yalcinalp & Gulbahar, 2010). Impersonalized learning can negatively affect learners’ attitudes because they do not relate to the content being studied (Howery et al., 2013).
Role of ICTs
Using the internet or e-learning is one approach than can make learning more personalized (Abik & Ajhoun, 2009). More specifically, Chen (2008) developed a genetic-based personalized e-learning system which allows learners to progress through online tutorials and activities at a personal pace. Specific needs are targeted with this tool because the database provides questions based on previous errors, therefore time is not wasted on concepts already mastered. Additionally, the instructor has access to student progress which facilitates their ability to provide personalized feedback. In another study, a computer-assisted program was used to personalize math problems from a textbook by inserting familiar names from a particular group of students (Chen & Liu, 2007). Learners connected with the personalized word problems and this process assisted their reading comprehension. Similarly, creating online student profiles to set learning goals is an essential step when using the e-learning INDeLER system (Jovanovic, Milosevic, & Zizovic, 2008). This program considers specific learning styles, prior knowledge, and “can be adapted to the individual learner, which is hard to achieve in the common teaching process” (p. 41).
Working online at a personalized pace was the most significant advantage described by middle school students in one study (Edwards & Rule, 2013). Other key benefits included the ability to start and stop videos when experiencing difficulties, to collaborate with peers, and to easily access online resources. Additionally, students expressed how they were not limited by time or space. Personalized online learning can be enhanced with virtual change agents; these human-like animated characters provide encouragement and suggest strategies when learners encounter difficult tasks (Kim, 2012). Furthermore, personalized learning can be achieved and aligns with the emergent popularity of Web 2.0 sites that favour user-generated content and collaboration (McLoughlin & Lee, 2010). In this context, learners have choices because tasks are “controlled by the individual, not the institution” (Hall, 2009, p. 33).
E-learning can be further personalized with mobile devices, or m-learning (Faulkner, 2013). Mobile devices help teachers meet specific needs of students, for example, learners with visual impairments can easily resize text (Faulkner, 2013). Using e-books supports personalized learning because students can search difficult words online and make personal notes while reading (Huang, Liang, Su, & Chen, 2012). In another study, students received smartphones to document an excursion and complete scientific research (Song, Wong, & Looi, 2012). Students found the experience highly personal because the devices provided a sense of control and ownership. Finally, the smallness and mobility of the devices encouraged sharing and collaboration in an authentic context. Mobile devices increase learning time for individuals because they can login anytime and anywhere (Nedungadi & Raman, 2012). Education combined with mobile technology enhances personalization because students “can take their learning to go” (McElvaney & Berge, 2009, p. 7).
Obstacles
The issue of cost is always an obstacle when dealing with ICT technologies (Abik & Ajhoun, 2009). However, the price of mobile phones is decreasing and may provide a cheaper alternative for schools who cannot invest in computer labs (Nedungadi & Raman, 2012). Many schools are adopting a BYOD (bring your own device) policy (Faulkner, 2013) which reduces the financial burden for schools because many students already own a mobile phone or tablet (Nedungadi & Raman, 2012). Regarding e-learning, there are many free technologies readily available online (McElvaney & Berge, 2009).
Some researchers argue that e-learning or m-learning can lead to students becoming distracted (Huang, Liang, Su, & Chen, 2012) due to the open nature of the internet (Chen, 2009). Although this is possible in some cases, the majority of students are more motivated and engaged when using personalized learning tools (Nedungadi & Raman, 2012; Chen & Liu, 2007). Setting up class groups for support (McLoughlin & Lee, 2010), designing a central website (Edwards & Rule, 2013), and structuring specific learning paths can keep students focused online while reducing the risk of cognitive overload (Chen, 2009).
There is concern that personalized learning is not effective for students who lack self discipline (Edwards & Rule, 2013). However, teachers can monitor progress online more closely when activities and discussions are documented (Chen & Liu, 2007). Online student profiles allow the instructors to teach each student exclusively (Jovanovic, Milosevic, & Zizovic). Kim (2012) also highlighted how providing timely feedback online can address students who lack discipline.
Works cited
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