This research was supported by a Federal Title II D Enhancing Education through Technology Program awarded to Barbara Signer by The New York City Department of Education.
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Professor-student interaction is critical for online learning to occur (Anderson & Garrison, 1995; Hillman, Willis, & Gunawardena, 1994; Signer, Holmes, & MacLeod, 2006). Frequent and constructive professor interactions have been acknowledged to contribute to successful asynchronous online learning (Berge, 1995; Salmon, 2000). However, an online interactive community of learners alone is not sufficient to promote reflective learning. Achieving high levels of learning relies on design, facilitation, and direction (Garrison & Cleveland-Innes, 2005). Various researchers have studied the online interactions between teacher-learner and have generated types of interactions that occur in the online learning environment to better understand the online learning process. Conceição (2006) discussed the importance of affective strategies in an online environment. These include providing feedback, encouragement, and support to learners. Anderson, Rourke, Garrison & Archer (2001) classified online teacher presence by three characteristics: course design and administration, facilitation of discourse, and direct instruction. In a study of over 3000 online course evaluations, Rossman (1999) reported that teacher responsibilities which facilitate discussions and encourage interaction were key to meaningful learning. Quiroz (2008), in studying tutor interventions in online teacher training, reported the following types of teacher feedback occurred most often: encouragement, information, connection to professional growth, questions asking for justification, and management for completing tasks.
In order to interpret the results of this study in light of previous findings, the researchers consulted the literature for studies that investigated how different levels of asynchronous online facilitation promoted learning. Many of the published studies involved categorizations applicable to situations in which students were required to reach consensus in order to solve a problem (Anderson & Garrison, 1995; Collison, Elbaum, Haavind, & Tinker, 2000; Duffy, Dueber, & Hawley, 1998). The courses in the current study did not involve such consensus building. The coding scheme developed by Angeli, Valanides, and Bonk (2003) was deemed most applicable to the current study. This coding method groups faculty strategies of instruction into low-level mentoring, high-level mentoring and management facilitation categories. According to Angeli et al. (2003), high-level mentoring refers to interactions that do not give students answers but instead provides scaffolding to develop deeper understanding. Low-level mentoring refers to social acknowledgement, general advice, feedback, direct instruction, specific questioning, and providing examples. Management applies to interactions that are associated with following directions and navigating the online course.