**3. Results and conclusion**

This section reports the results from the project so far and makes conclusions that were possible at the end of phase 1 of this project. The reported results are mainly from the one school that had already embraced the online supervision model as it was in its formative stage and was using the course area created by the project team.

#### **3.1. Results**

two students purposively selected. A team of administrators representing school of graduate studies, the eCampus, school coordinators, and technical team leaders were to brainstorm and harmonize policy and procedures for online supervision of postgraduate research at Maseno University. The project secretariat were to use the final protocol developed to train supervisors towards building a collaborative learning environment for postgraduate research students and

During piloting, data were collected and used to make adjustments in the protocols. Policy documents were then discussed, reviewed, and consultations will be made to determine the extent to which they support implementation of the protocol and areas that need to be harmonized. A validation workshop was held with relevant stakeholders before preparing a final report containing the revised supervision protocol and the necessary policy revision for

The following activities (see figure below) will be undertaken in a bid to operationalize the project with the help of a research secretariat composed of four researchers. Each associate researcher will be in charge of two schools having postgraduate studies at the eCampus. Besides overseeing the school activities, they will also assist with specialized areas like creating the collaborative platform, training of supervisors, and engaging with university management. The actual project plan will be carried out in the steps set out in the figure that follows:

It is expected that at the completion of this project, Maseno University would have developed a policy for blended post graduate supervision; at least 50% (Based on the number of schools offering courses online) of the lecturers undertaking post graduate supervision would have been trained to undertake online supervision of postgraduate students. A reviewed supervi‐ sion policy for online supervision of postgraduate students will be available for use by all

their supervisors at Maseno University.

384 E-Learning - Instructional Design, Organizational Strategy and Management

implementation.

**2.6. Project plan**

**Figure 2.** projected Project Plan

**2.7. Expected outcomes**

It should be noted that the project being reported is a work in progress and will take time to complete. The results reported here refer to what has been achieved so far. The project objectives had been set as follows:


The results being reported in this book therefore are what has been achieved so far as the project continues on.

#### *3.1.1. Managing the supervision milestones*

The analysis of data collected was done through a time series analysis on trends of supervision milestones [12], which gave provided the results presented using the graph that follows in terms of postgraduate supervision in research. To arrive at the four key issues analyzed for trends, online interviews were done to help arrive at possible areas of need for the students.

The trends were analyzed from data collected from students in four successive semesters (Categories 1 to 4) through a five-scale rated discussion and questionnaire. The responses were rated with respect to assistance given to students in drafting concept paper and proposal (series 1), provision of tools to support the research process (series 2), identifying with a research team (series 3), and exposure to seminars and presentations (series 4).

It is apparent from the trends that the main supervision milestones given in order of preference were as follows: exposure to research seminars and presentations (4.325), giving students' assistance in drafting an acceptable concept paper and proposal (3.95), provision of adequate

tools to support the research process (2.4), and identifying with a collaborative research team (2.225).

The milestones are further discussed below in order of preference from the research outcomes:


#### *3.1.2. Building a collaborative learning environment*

The table below gives a list of issues raised by postgraduate students after their course work


Looking closely at the issues raised by the students, it is apparent that all the issues would be adequately dealt with by having a chance to interact with peers and supervisors.

This researcher used a novel method for converting educational log data collected by observing learner interactions in the course into features suitable for building predictive models of student success as reported by [26]. They further acknowledge that unlike cognitive modeling or content analysis approaches, these models are built from interactions between learners and resources, an approach that requires no input from instructional or domain experts and can be applied across courses or learning environments. It is from the results of these analyses that a model of interaction was suggested for the eCampus. The model is presented in the diagram that follows.

**Figure 3.** Post Graduate Students' Interactions

tools to support the research process (2.4), and identifying with a collaborative research team

386 E-Learning - Instructional Design, Organizational Strategy and Management

The milestones are further discussed below in order of preference from the research outcomes:

**i.** Giving students assistance in drafting an acceptable concept paper and proposal. This

**ii.** Provision of adequate tools to support the research process. This is because the main

**iii.** Identifying with a collaborative research team. From the questionnaire, it was

**iv.** Exposure to research seminars and presentations. All schools involved in this project

innumerable communication, learning, and interactive tools.

is mainly because the research area has interactive and self-directing instructions together with resources that allow learners to discuss and learn from each other.

tool used in the postgraduate research area is an LMS used at the eCampus, which is supported by Moodle. Therefore, all the interactive tools in-built in the Moodle and web2 tools supported by Moodle are available for online supervision. Moodle has

reported by all the students surveyed that most postgraduate students are isolated and lonely. Looking closely at the issues raised by the students, it is apparent that all these issues would be adequately dealt with by having a chance to interact with peers

resorted to holding seminars and presentations during the face to face meeting held once a term by the eCampus. This practice brought about learning in the process of presentations. Students ask questions which are tackled jointly by all faculty members

(2.225).

and supervisors.

present.

Quality interaction and feedback from supervisor and peers was one of the emerging practices realized from building a collaborative learning environment. This came about because the course area is open to all postgraduate students and other supervisors; therefore, a supervisor is compelled to ensure the feedback they give is holistic and humane. The interactions identified in the postgraduate research area so far may be symbolized by the diagram that follows.

It is clear from the diagram that the depicted interaction is not only between the student and the supervisor but also between the student and the content as well as among the peers. It results in a win–win situation for all involved as supervisors get to improve their skills by interacting not only with learners but also with content availed in the research area. Students on the other hand get assistance from other supervisors interacting in this common area.

#### *3.1.3. Emerging research outcomes*

The qualitative data reviewed from the lecturers taking part in this project resulted in signif‐ icant outcomes that cannot fully be ignored. These had to do with schools thinking of novel ways of mitigating against the high learner to supervisor ratio. It emerged that the project school had only four qualified lecturers against 85 students needing supervision after com‐ pleting course work. They took advantage of the existing interactive course area to outsource for supervisors external to the department and the university who needed the experience and could spare time to assist with the supervision tasks.

Furthermore, the logit model was used to predict the learner completion rates and expected research outputs from the postgraduate students. For these predictions to be possible, the outcome (response) variable is binary, i.e., complete or drop out (1 or 0). The predictor variables of interest are as follows: frequency of contact with supervisors, interaction with peers, online tools support provided, and identification with a research team. Categories in the curve refer to semesters when the data are collected. The predictor logistic line is presented below:

The results indicated that a learner is likely to complete research in four semesters, which is just over a year if all the predictor variables are present (series 2). At the same time, the research outputs are likely to increase by slightly more than 50% (series 1). These outputs range from publications to presentations at conferences and seminars to innovative outputs.

### **3.2. Conclusion**

Quality interaction and feedback from supervisor and peers was one of the emerging practices realized from building a collaborative learning environment. This came about because the course area is open to all postgraduate students and other supervisors; therefore, a supervisor is compelled to ensure the feedback they give is holistic and humane. The interactions identified in the postgraduate research area so far may be symbolized by the diagram that

It is clear from the diagram that the depicted interaction is not only between the student and the supervisor but also between the student and the content as well as among the peers. It results in a win–win situation for all involved as supervisors get to improve their skills by interacting not only with learners but also with content availed in the research area. Students on the other hand get assistance from other supervisors interacting in this common area.

The qualitative data reviewed from the lecturers taking part in this project resulted in signif‐ icant outcomes that cannot fully be ignored. These had to do with schools thinking of novel ways of mitigating against the high learner to supervisor ratio. It emerged that the project school had only four qualified lecturers against 85 students needing supervision after com‐ pleting course work. They took advantage of the existing interactive course area to outsource for supervisors external to the department and the university who needed the experience and

Furthermore, the logit model was used to predict the learner completion rates and expected research outputs from the postgraduate students. For these predictions to be possible, the outcome (response) variable is binary, i.e., complete or drop out (1 or 0). The predictor variables of interest are as follows: frequency of contact with supervisors, interaction with peers, online tools support provided, and identification with a research team. Categories in the curve refer to semesters when the data are collected. The predictor logistic line is presented below:

follows.

*3.1.3. Emerging research outcomes*

could spare time to assist with the supervision tasks.

388 E-Learning - Instructional Design, Organizational Strategy and Management

In conclusion, it was noteworthy that the project enabled the university to arrive at the following in its phase 1 of implementation:


With all these initiatives taking place through the eCampus, the final outcome from this project is expected to be a policy document being formulated based on research outcomes to guide blended research processes on blended supervision.
