E-tutorial
E-tutorial
Christopher Warren, Memorial University of Newfoundland
Definitions and background
An E-tutor (or an automated tutor) as a software tool that offers “students guidance in undertaking specific tasks” (Albert & Thomas, 2000, p. 141). Curilem, Barbosa and Azevedo (2007) determined three different approaches to e-tutor design; the first approach uses the e-tutor as a guide where the software has control of the lesson; the second approach has the student in control of where the lesson will lead, and the third approach has a mixture of the first two, where the system will determine the level of intervention based on student responses (p. 548). Some tutorials will simply guide the user through a set a resources to help complete a specific assignment (Albert & Thomas, 2000). Resources such as videos are becoming a popular resource in these tutorial programs (van der Meij & van der Meij, 2014). Other e-tutors can be much more complex and interactive. Many e-tutors are interactive, can adjust for skill level, and will offer random content to challenge the learner (Adams, Yin, Vargas, Luis, & Mullen, 2014). Other programs will offer “scaffolding”, which attempts to mimic a human tutor by assisting the learner (Albert & Thomas, 2000, p.143). This assistance can be enhanced by smart ‘learning’ e-tutors, that build on previous data to improve suggestions in the future (Barnes & Stamper, 2010, p.11). Whetstone, Clark, and Flake (2014) noted that e-tutors are often used to assist a human teacher to adjust their instruction based on the data collected by the e-tutor.
Affordances
According to Dalal (2014), an e-tutorial allows for multimedia to be used to introduce complex topics in a manner that is convenient for the learner (p.366). For example, in computer technology training, video tutorials can allow for sequential steps to be displayed on a screen at a pace good for the learner (van der Meij & van der Meij, 2014). Video tutorials can also be tailored and adjusted as needed; narration can accompany video, which Winslow, Dickerson and Lee (2012) argue can improve learning. W u, Lin, and Yang (2013) also observed that a text-based e-tutorial is convenient for the learner; text-based discussion allow for the student to pick a convenient time and place to get assistance (p.53). Computer-guided oral reading allows for more time practising reading aloud than with a human being (Mostow, Nelson-Taylor & Beck, 2013).
A study by Curilem et al. (2007) noted that “A key function of any ITS (Intelligent Tutor System) is the ability to adapt, as closely as possible, pedagogical activities to individual student/learner needs” (p.546). Tutoring programs can “assess, guide, and provide advice to learners without human input” (Fournier-Viger, Faghihi, Nkambou & Engelbert, 2010, p.17). Crosby and Iding (1997) found adaptive tutorials that can be designed around certain personality types of the learner. Conversational computerized tutoring systems can adapt during a lesson in an objective manner (Latham, Crockett, McLean & Edmonds, 2012). An e-tutor can easily resist the human temptation to give an answer, and patiently wait for the student to think for themselves and give the answer (Latham et al., 2012). Computer programs can avoid human bias when tutoring, especially “stigmatizing below-grade-level readers” (Mostow et al., 2013, p.251). E-tutorials allow for tutoring to be tailored to an English Language Learner’s cultural background so that they have culturally-familiar examples when learning English, allowing for students to focus on learning a new language rather than a new language and culture simultaneously, which can overwhelm an ELL student (Poulsen, Hastings, Allbritton , 2007).
Van Laarhoven et al. (2008) observed teachers viewing e-tutorials for assistive technologies, so that they can evaluate and become comfortable with the technology before classroom deployment. Some e-tutors can mark student assessments (such as writing summaries) for human teachers so that the teacher can offer more practice for the student, while freeing up the teacher for other tasks in the teaching-learning process (He, Hui & Quan, 2009). Automated software can help human tutors practice their tutoring skills with a virtual tutor (Walker, Rummel, Koedinger, 2011).