Salukinet d2l

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Southern Illinois University Extended Campus uses six IT systems that I can name (Salukinet, Banner 9, Slate, D2L, Morris Library System, PeopleSoft), but overall, I would guess there are at least a dozen. The two specific IT systems discussed below are Distance 2 Learn (D2L) and PeopleSoft.

The lead for D2L (the learning management system also called SIU Online) is the Curriculum and Development Committee for the content and design, which is comprised of several university college departments. Of course, there is heavy collaboration with the IT department.

The lead for PeopleSoft, an e-business human resource management system, is the HR department. I am unaware if this software includes the financials and supply chain management package. I know the software is used to manage employee benefits and payroll.

Using the IT theory, Model of PC Utilization (MPCU), can help determine if the system is working as needed, and successful.

MPCU predicts individual usage behavior and individual acceptance of technology using the following Core Constructs (Venkatesh et al., 2003). The two IT systems are analyzed below:

Core Constructs

D2L

PeopleSoft

Job-fit

Highly useful, SIU online depends on this technology to enhance performance and deliver instruction.

Inadequate, perhaps the wrong package was implemented. Supervisors are to manually calculate employee’s accrued leaved, etc.

Complexity

Improved, the dashboards are user friendly.

Only the essential functions seem to be understood.

Long-term Consequences

Shown expansion and use via hybrid classes and with more offerings available online.

Great for complex payroll entries and easing HR workload, which helps department focus on other tasks.

Affect Towards Use

Pleasurable experience with users.

Mixed feelings.

Social Factors

Acceptable, the online learning culture has become more popular.

Suitable, HR functions are dependent on this technology and is the norm.

Facilitating Conditions

Orientation classes available

Tutorials and trainings provided

The MPCU model suggests that a system is more useful and successful if individuals believe that using the technology can make their job easier and gain performance. Additionally, the technology should be user-friendly, have long-term benefits, and be accepted among the organizational culture. With those factors in mind, D2L reveals a better score compared to PeopleSoft.

Note: I admit that there is some bias above since I am unfamiliar with PeopleSoft, whereas I have broadened perspective as a student and instructor with the D2L system.

Reference: Venkatesh, V., Morris, M. G, and Davis, F. D. (2003). User Acceptance of Information Technology : Toward a Unified View, MIS Quarterly, 27(3), 425-478

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Case study methodology has long attracted the attention of methodologists and contested terrain in social sciences, which is visualized by variant and sometimes opposing approaches adopted by many researchers. Despite case studies being one of the frequently applied qualitative methodologies of research, researchers do not have full autonomy in designing and implementing variant case studies (Houghton et al., 2015). Considering the readings for the module, the three key ideas that were most significant entailed:

1. Plausible rival explanation's role.

2. Comparing the cased-oriented approach with the variable-oriented approach in the design and conduct of case study research.

3. The link between research on case studies and qualitative research.

According to Robert Yin (2017), in the sixth edition of the book "Case Study Research and Applications," the availability of rival details in the design and conduct of case study research remains a crucial element. In plausible rival explanations, the hurdle comes in identifying and addressing the most plausible rivals instead of necessarily dealing with them (Yin, 2017). The second key idea dwells on the holistic aspect of the case under scrutiny as it represents a fundamental element of case study research (Wodak, 2015). The focus is on comprehension of "the case" on the facets of what it is, how it works, and the interaction with the real-world contextualization environment (Roller, 2019). The third statement explores the evident link between qualitative research and case study research, in which it can be asserted that the inclusion of case study on qualitative research tends to bring out the notion of it could be undertaken as one among the acceptable variants in conducting qualitative research (Yin, 2017).

I want to explore qualitative content analysis and discourse analysis as the two case study data analytic techniques. The content analysis research tool will help determine the presence of aspects of words, concepts, or themes within the given qualitative data context (Houghton et al., 2017). Therefore, I would like to explore further how possible it is to quantify and analyze the most probably evident themes, concepts, and specific words that reveal themselves when the content analysis is applied. The data source might arise from open-ended questions, conversations, notes on field research, and interviews; hence, a single study could analyze numerous facets of texts in its analysis (Kuckartz, 2019).

To effectively analyze the book, it is better to break down the text into manageable codes to summarize the data (Roller, 2019). Additionally, I would like to explore discourse analysis further as it entails studying written or spoken language in a social context. Moreover, this technique is critical for numerous reasons. It defines the question and chooses the content of analysis, gathers content and theory on the aspect, analyzes the information for themes variant patterns, and then reviews the results to conclude.

In the analysis of the data, there is the concept that seems a hurdle grasping; the idea of OTTR (that implies "observe," "think," "test," and "revise"). Analysis of data in case studies might seem unusual from the norm as much of the collected data is qualitative (Wodak, 2015). What seems challenging to grasp is how the OTTR concept helps shape subsequent data collection as the analysis ought to be interactive. In "observe," the concept dictates that the initial observations be enacted with the hypothesis's concurrent formulation. Under "think," appropriate consideration is factored into what extra information is supposed to be collected in ruling out alternatives (Houghton et al., 2015). Under "test," further information is meant to be collected via reviews and subsequent observations. Under the last facet of "revise," the ensuing comments are analyzed, and assessments are undertaken to reexamine the initial hypothesis. Therefore, as can be asserted from the above conclusive paragraphs, case studies' analysis is a challenging task. Hence, it requires adequate allocated time in comprehensively understanding the activity under review to attain efficient results.

References

Houghton, C., Casey, D., & Smyth, S. (2017). Selection, collection and analysis as sources of evidence in case study research. Nurse Researcher, 24(4), 36-41.

Houghton, C., Murphy, K., Shaw, D., & Casey, D. (2015). Qualitative case study data analysis: An example from practice. Nurse Researcher, 22(5), 8-12.

Kuckartz, U. (2019). Qualitative text analysis: A systematic approach. In G. Kaiser, N. Presmeg, Compendium for Early Career Researchers in Mathematics Education. ICME-13 Monographs. Springer.

Roller, M.R. (2019). A quality approach to qualitative content analysis: Similarities and differences compared to other qualitative methods. Forum: Qualitative Social Research, 20(3), 31.

Wodak, R. (2015). Critical discourse analysis, discourse‐historical approach. In The International Encyclopedia of Language and Social Interaction (pp.1-14). John Wiley & Sons

Yin, R. K. (2017). Case study research and applications: Design and methods. Sage Publications.

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