The Invisible Interface: MS Word in the Writing Center

Writing centers have developed best practices in order to help student writers, most popularly, non-directive tutoring pedagogies, based on the use of paper drafts. These same tutoring protocols have been extended to computer-based face-to-face sessions under the assumption that they will have similar outcomes, which subscribes to the myth of technology as a transparent tool that does not affect the writing that emerges from it. A lack of attention to computers in the writing center extends to the use of word processing programs like MS Word. This article discusses these issues in the context of a case study of one tutor in computer-based tutoring sessions in a writing center. Throughout these sessions, situations arose involving the use of the MS Word interface that affected the nature of the session itself. This case study suggests that computers, and particularly the MS Word program, need to be examined critically to consider how their use corresponds with the mission of the writing center itself. There are a number of strategies that can also help tutors use MS Word in ways that will best serve students’ individual needs.     

Situation Definition and the Online Synchronous Writing Conference

Since the mid 1990's, more and more college and university writing centers have been offering online synchronous writing conferences to students. Writing center researchers have published extensively on how tutors can promote collaboration in online conferences, but comparatively few have used Lev Vygotsky's conception of the zone of proximal development (ZPD) to analyze activity in these conferences or to develop specific methods for working with students in these environments. Using more recent developments in the theory of the ZPD, such as the concept of situation definition, I will discuss how tutors can apply strategies related to the ZPD to promote student learning. By focusing on students’ definitions of rhetorical concepts that often implicitly guide students’ writing processes, tutors can help students improve how they approach their writing tasks. Progress through the ZPD, then, is more related to how students grow their own understanding, rather than on the correcting of students’ texts. I will illustrate this theoretical discussion by presenting examples of two online synchronous writing conferences, and I will describe the implications and possible shortcomings of a method of tutoring that applies the concept of situation definition and the ZPD.     

Tutoring executives online: what drives perceived quality?

Studies of learning and student satisfaction in the context of online university programmes have largely neglected programmes catering specifically to business executives. Such executives have typically been away from higher education for a number of years, and have collected substantial practical experience in the subject matters they are taught. Their expectations in terms of both content and delivery may therefore be different from non-executive students. We explore perceptions of the quality of tutoring in the context of an online executive MBA programme through participant interviews. We find that in addition to some of the tutor behaviours already discussed in the literature, executive students look specifically for practical industry knowledge and experience in tutors, when judging how effective a tutor is. This has implications for both the recruitment and training of online executive MBA tutors.     

The development of an ESL OWL, or learning how to tutor writing online

This essay describes the development of an ESL OWL by grounding practices in language and literacy pedagogy theory. An initial discussion explores OWLs emulating physical writing center spaces. Two areas of concern are then addressed in meeting the needs of second language writers as they relate to practices and training for online tutoring: error correction—an area of frequent concern to second language writers—and increased interactivity—meeting second language writer expectations and creating autonomous learners. Issues of plagiarism by second language writers are discussed as related to the type of feedback OWL tutors can provide. Highlighted throughout are samples of interactions between tutors and writers that show a process of learning how to create dialogue rather than dictations from the tutor to clean up a single essay.     

Creating cognitive tutors for collaborative learning: steps toward realization

Our long-term research goal is to provide cognitive tutoring of collaboration within a collaborative software environment. This is a challenging goal, as intelligent tutors have traditionally focused on cognitive skills, rather than on the skills necessary to collaborate successfully. In this paper, we describe progress we have made toward this goal. Our first step was to devise a process known as bootstrapping novice data (BND), in which student problem-solving actions are collected and used to begin the development of a tutor. Next, we implemented BND by integrating a collaborative software tool, Cool Modes, with software designed to develop cognitive tutors (i.e., the cognitive tutor authoring tools). Our initial implementation of BND provides a means to directly capture data as a foundation for a collaboration tutor but does not yet fully support tutoring. Our next step was to perform two exploratory studies in which dyads of students used our integrated BND software to collaborate in solving modeling tasks. The data collected from these studies led us to identify five dimensions of collaborative and problem-solving behavior that point to the need for abstraction of student actions to better recognize, analyze, and provide feedback on collaboration. We also interviewed a domain expert who provided evidence for the advantage of bootstrapping over manual creation of a collaboration tutor. We discuss plans to use these analyses to inform and extend our tools so that we can eventually reach our goal of tutoring collaboration.     

Toward an Affect-Sensitive AutoTutor

Here, we consider the possibility of enabling AutoTutor, an intelligent tutoring system, to process learners' affective and cognitive states. AutoTutor is a fully automated computer tutor that simulates human tutors and converses with students in natural language.     

Cross‐age peer tutors in asynchronous discussion groups: studying the impact of tutors labelling their interventions

Cross‐age tutors were randomly assigned to one of the three tutor training conditions distinguished for the current study: (1) the labelling experimental condition, characterized by requirements to label their tutor interventions, based on the e‐moderating model of Salmon; (2) the non‐labelling experimental condition, focusing on tutor's acting upon the role of an e‐moderator without preliminary requirements with regard to labelling the phase of e‐moderating in their messages; and (3) a control condition, typified by all‐round information on online facilitation. The results indicated that tutors are not really capable in labelling their interventions accurately. Nevertheless, labelling did foster enhanced e‐moderating activities. Compared to tutors in the control condition, tutors in the experimental conditions performed at a higher level, implying that they adopted more balanced tutor support. Labelling did not result in a differential impact on self‐efficacy and perceived collective efficacy.     

Email small group peer review revisited

Attention to email exchanged among a small group of student peers supercedes discussion of networked computer labs and is distinguished from research on collaborative classroom work in general, on online peer tutoring in writing centers, on email communication in online professional writing courses, and on online discourse in general. Email peer response within small groups is different from larger-scale, one-to-many computer-based communication tools (CBCT) on class mailing lists, bulletin boards, blogs, and wikis on the one hand and smaller-scale, one-to-one email exchange between an individual student and a peer tutor on the other hand. The benefits of assignments that require small groups to respond electronically and asynchronously to each other's drafts are analyzed and illustrated: rhetorical/thematic, discursive/environmental, technological, logistical/time management. The practicalities of students’ exchange of drafts, deadlines, and other guidelines are explained and illustrated in typical student email responses and model instructor handouts.     

Cross-age peer tutors in asynchronous discussion groups: Exploring the impact of three types of tutor training on patterns in tutor support and on tutor characteristics

This study was conducted in an authentic university setting with fourth-year Educational Sciences’ students operating as online peer tutors to facilitate freshman tutees’ online collaboration and knowledge construction in a blended “Instructional Sciences” course. Taking into account prior research uncovering weaknesses in online peer tutor behaviour, the aim of the study was to explore the possibility to optimise the quality and the nature of online peer support. In this respect, the study examined the impact of three tutor training conditions (multidimensional support, model/coach, and control condition) on peer tutors’ actual tutor behaviour in asynchronous discussion groups and on tutors’ self-efficacy beliefs, perceived collective efficacy, and training evaluation. Quantitative content analysis was applied to study online peer tutor behaviour. More specifically, two coding schemes were used focusing respectively on the occurrence of different e-moderating activities and on the evolution from modeling to coaching behaviour. Tutors’ self-efficacy beliefs, perceived collective efficacy, and training evaluation were assessed by means of questionnaires.     

Designing automated adaptive support to improve student helping behaviors in a peer tutoring activity

Adaptive collaborative learning support systems analyze student collaboration as it occurs and provide targeted assistance to the collaborators. Too little is known about how to design adaptive support to have a positive effect on interaction and learning. We investigated this problem in a reciprocal peer tutoring scenario, where two students take turns tutoring each other, so that both may benefit from giving help. We used a social design process to generate three principles for adaptive collaboration assistance. Following these principles, we designed adaptive assistance for improving peer tutor help-giving, and deployed it in a classroom, comparing it to traditional fixed support. We found that the assistance improved the conceptual content of help and the use of interface features. We qualitatively examined how each design principle contributed to the effect, finding that peer tutors responded best to assistance that made them feel accountable for help they gave.     

COMET: A Collaborative Tutoring System for Medical Problem-Based Learning

This paper discussed about the developed collaborative intelligent tutoring system for medical PBL called Comet (collaborative medical tutor). Comet uses Bayesian networks to model the knowledge and activity of individual students as well as small groups. It applies generic tutoring algorithms to these models and generates tutorial hints that guide problem solving. An early laboratory study shows a high degree of agreement between the hints generated by Comet and those of experienced human tutors. Evaluations of Comet's clinical-reasoning model and the group reasoning path provide encouraging support for the general framework.     

International on-line reciprocal peer tutoring to promote modern language development in primary schools

The paper reports data from an on-line peer tutoring project. In the project 78, 9–12-year-old students from Scotland and Catalonia peer tutored each other in English and Spanish via a managed on-line environment. Significant gains in first language (Catalonian pupils) modern language (Scottish pupils) and attitudes towards modern languages (both Catalonian and Scottish pupils) were reported for the experimental group as compared to the control group. Results indicated that pupils tutored each other in using Piagetian techniques of error correction during the project. Error correction provided by tutors to tutees focussed on morph syntaxys, more specifically the correction of verbs. Peer support provided via the on-line environment was predominantly based on the tutor giving the right answer to the tutee. High rates of impact on tutee corrected messages were observed. The implications for peer tutoring initiative taking place via on-line environments are discussed. Implications for policy and practice are explored.     

Diagnosing and acting on student affect: the tutor’s perspective

In this paper we explore human tutors’ inferences in relation to learners’ affective states and the relationship between those inferences and the actions that tutors take as their consequence. At the core of the investigations presented in this paper lie fundamental questions associated with the role of affective considerations in computer-mediated educational interactions. Theory of linguistic politeness is used as the basis for determining the contextual factors relevant to human tutors’s actions, with special attention being dedicated to learner affective states. A study was designed to determine what affective states of the learners are relevant to tutoring mathematics and to identify the mechanisms used by tutors to predict such states. Logs of tutor-student dialogues were recorded along with contextual factors taken into consideration by tutors in relation to their specific tutorial dialogue moves. The logs were annotated in order to determine the types and range of student and tutor actions. Machine learning techniques were then applied to those actions to predict the values of three factors: student confidence, interest and effort. Whilst due to limited size and sparsity of data the results are not conclusive, they are very valuable as the basis for empirically derived hypotheses to be tested in further studies. The potential implications of the hypotheses, if they were confirmed by further studies, are discussed in relation to the impact of tutor’s ability to diagnose student affect on the nature of computer-mediated tutorial interactions.     

Weathering wikis: Net-based learning meets political science in a South African university

Wikis represent flexible tools functioning as open-ended environments for collaboration while also offering process and group writing support. Here we focus on a project to innovate the use of wikis for collaborative writing within student groups in a final-year undergraduate political science course. The primary questions guiding our research were in what ways could wikis assist collaborative learning in an undergraduate course in political science and how we could support educators’ in the effective use of wikis? Curiously, wikis may serve as a mediating artifact for collaborative writing even among students who are reluctant to post online drafts. The paper raises questions concerning the nature and limits of lecturer and tutor power to deliver transformative educational innovations in relation to the capacity of students to embrace, comply with, or resist such innovation. In analysing the negotiation of the use of wikis in the course by and among the lecturer, tutors, and students, we draw on two principles in activity theory, which Yrjö Engeström argued are central to his model of expansive learning: multi-voicedness and contradictions [Engeström, Yrjö. (1987). Learning by expanding: An activity-theoretical approach to developmental research. Helsinki: Orienta-Konsultit; Engeström, Yrjö. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of Education and Work14(1), 133-156.]. We add a third principle, transparency, to more fully capture what we observed.     

Managing programmed instruction and collaborative peer tutoring in the classroom: Applications in teaching Java™

To fulfill part of the course requirements, 34 undergraduate students in two courses completed an online programmed instruction tutor as the first technical training exercise in a Java™ programming course designed for information systems majors. The tutor taught a simple JApplet program to display a text string within a browser window on the Web. Students in the first course next participated in a collaborative peer tutoring session, based on the JApplet program, followed by a lecture on the program and by successfully running the program on the Web. For the second course, the peer tutoring session was scheduled after the lecture and after successfully running the program. Students in both courses completed tests of far transfer (“meaningful learning”) and software self-efficacy before using the tutor and on several subsequent occasions following that initial learning. Students in the second course also completed a 4-item scale to assess the development of classification and functionality knowledge regarding elements of the program. Students in both courses showed progressive improvement in all performance measures across the several assessment occasions. Students’ positive ratings of the effectiveness of both the tutor and the collaborative peer tutoring supported the value of these learning experiences in a technical knowledge domain. The results of this study, based on student performance observed within the context of the classroom, show the importance of providing a range of synergistic learning experiences that culminate in a level of skill and confidence that prepares and motivates all students for advanced instruction in Java. They also show how to manage the instructional techniques in the classroom to accomplish that educational outcome.     

Evaluation of a meta-tutor for constructing models of dynamic systems

Modelling is an important skill to acquire, but it is not an easy one for students to learn. Existing instructional technology has had limited success in teaching modelling. We have applied a recently developed technology, meta-tutoring, to address the important problem of teaching model construction. More specifically, we have developed and evaluated a system that has two parts, a tutor and a meta-tutor. The tutor is a simple step-based tutoring system that can give correct/incorrect feedback on student's steps and can demonstrate steps for students when asked. Because deep modelling requires difficult analyses of the quantitative relationships in a given system, we expected, and found, that students tended to avoid deep modelling by abusing the tutor's help. In order to increase the frequency of deep modelling, we added a meta-tutor that coached students to follow a learning strategy that decomposed the overall modelling problem into a series of “atomic” modelling problems. We conducted three experiments to test the effectiveness of the meta-tutor. The results indicate that students who studied with meta-tutor did indeed engage in more deep modelling practices. However, when the meta-tutor and tutor were turned off, students tended to revert to shallow modelling. Thus, the next stage of the research is to add an affective agent that will try to persuade students to persist in using the taught strategies even when the meta-tutoring and tutoring have ceased.