The Difference in Information Seeking Patterns Between Faculty and Graduate Students - Paper Example

There have been numerous researches exploring the difference in information seeking patterns between faculty and graduate students in different disciplines.  However, the same has not been done for undergraduates. The study explores the information seeking patterns in this group. The problem statement is open-ended and unbiased.  By exploring the patterns of undergraduate students in their entirety, the researcher avoids limiting the answers which can cause bias.  Given that previous research of a similar nature has been carried out successfully, the problem the research is exploring can also be solved. Additionally, patterns are specific enough to be measurable, hence making the problem solvable. There are also a limited number of ways to find information.  Therefore, the answers will not be infinite.

Definitions

Biglan model is a term used repeatedly in the text. This term has been sufficiently and clearly explained, together with other terms that arise from it, such as hard and soft disciplines. The definitions do not include the term in their explanations, hence there are not circular. These terms can be used by other researchers as they are not limited to the authors interpretation. These definitions are conceptual as they are based on a theory.

Literature Review

Although the author uses recent works in the literature review, most of the works are a bit old. The researcher explores the use of Biglans typology in studying disciplinary differences in several areas in higher education. However, all the works provided shed a positive image on this model, and there are no works of literature provided that challenges the use of the model or difficulties in using the model to investigate differences among disciplines. The probable cause for the expected results is provided y exploring studies that used the same model in their studies. Although the studies focused on the graduate and faculty behavior, the findings of these researchers can be used to predict the results of the authors study.

The author has not explained the findings by other researchers. However, a historical basis has been provided. The author chose to use Biglan model as it was a theoretical framework that had been tested and verified through empirical research. Additionally, the author provides a history of how it has been used by other researchers in investigating related problems.

Variables

The variable in this study included (1) background characteristics, (2) academic discipline/major, and (3) information-seeking behavior. These variables cannot be changed or manipulated due to the nature of the study. The study is observational hence the researcher has no control over any of this variables, but uses information collected to test his/her hypothesis. The researcher can only observe any difference or similarities that arise. The author uses data that was compiled previously and does not need to alter any variable to test his hypothesis. Changing the variables would invalidate the study.

Hypothesis

Differences in the various dimensions of the academic disciplines produce differences in information-seeking behavior. This hypothesis is directional as it predicts that a difference in the information seeking pattern of the undergraduates will differ due to the variation in their disciplines. The hypothesis is related to the statement of the problem as it proposes the expected results to the behavioral patterns of the undergraduates.

2. Methodology

Population

The population under study was the 10000 undergraduate students attending 38 4-year institutions. This population makes sense as four-year institutions are where one can get the variety of disciplines that will fit into the Biglans model.

Sample

The researcher states that 5175 students were selected from the 10000 student population. These students all studied in various colleges offering 4-year programs. These institutions included research and doctoral universities, comprehensive colleges and universities, and liberal arts colleges. Although the sampling was not random, the sampling technique used cannot be a source of bias. The nonrandomness of the sample is necessary for case study research as the researcher is concerned with the sample that is relevant to the study to make the relevant observations. The author uses Biglan model as the theoretical framework informing the research hence all the students chosen should be studying relevant courses, necessitating the use of purposive sampling. Randomly choosing students would have resulted in having some students taking disciplines not relevant to the study. The size of the sample was large enough. The researcher used all the students from the population that fit the purpose of the study.

Data Gathering

The data gathering method used was documentation review. The researcher obtained data from the 1996 College Student Experiences Questionnaire (CSEQ) collected through Indiana University's Center for Postsecondary Research & Planning. The CSEQ was used to get the information concerning the discipline, information gathering behavior, gender and race of the students. This method is simple, straightforward, and clearly explained hence it can be easy to replicate it.

Instrumentation

The instrument used was College Student Experiences Questionnaire (CSEQ). This is a document that measures the time and effort that is used by students in carrying out school-related activities. This instrument was not created for the study but is appropriate and it contains all the information the researchers required to carry out the study. It had the discipline majored by every correspondent, their gender, race, year of study, information seeking patterns, formatted like a questionnaire. Given the nature of the study, the questionnaire could not be tested to work out the problems. The type of the questions in the information seeking sections is appropriate and can be effectively used to construct a pattern in the behavior of the sample.

Method

The research uses the Biglan model to study the students interest in seeking information. The model breaks down the academic disciplines into three dimensions. The dimensions include hard versus soft, pure versus applied, and life versus nonlife. The study sought to determine whether there were differences in information seeking patterns in disciplines along this model.

Mests was used to determine if there were significant differences in the information-seeking behavior patterns of students majoring in academic disciplines along Biglan's dimensions. This instrument was not created for the study but is an already established method for determining the difference in mean between groups. Given that the study aimed to study the difference and extent of the difference in information seeking behavior of students in various disciplines, this instrument is appropriate.

3. Results

All the results have been clearly provided both in the form of tables and a narrative. The findings in the study are attributed both to the data found and the type of sample. Other observations such as the frequency of information seeking in students regardless of their discipline major were attributed to the instrument used. The questionnaire only covered the use of physical libraries. As such, the number of students seeking information may have increased if the data included other ways of researching. The results are clear and concise, and there is no confusing unimportant information provided.

Conclusions

The study found significant differences between various academic disciplines along the Biglans model. It found that the non-life, hard and applied disciplines had the east information seeking activities. Engineering fell under this category. Soft pure and life sciences had the most information seeking activities, and social sciences fell into this category. The study all found relevance in using the Biglans model in determining differences in information patterns across disciplines. The researcher compared the findings with previous findings and explained the discrepancies and similarities. For instance, there were differences in the patterns of the undergraduates and those found by other researchers between graduates and faculty. Given that the population studied differed, the researcher concluded that the results would also vary. Additionally, the majority of the students in the sample were first years who may need more assistance carrying out research as opposed to other students.

However, there are no alternative explanations provided and set aside. Although an explanation I provided for the difference, there is no explanation for the similarities. On the other hand, the conclusions are supported by the data. The hypothesis drawn by the researcher was proven true. The alternative hypothesis that there would be differences between the disciplines was accepted. Consequently, the null hypothesis was rejected. There were significant differences at the calculated P-value of 0.001 and 0.005. Although the researcher did not explicitly conclude this, the findings show that the null hypothesis was rejected.

5. Recommendations

The author recommends further study on the information seeking behavior of faculty and undergraduate students. This s a justified recommendation as there was no research concerning the topic at the time. Additionally, it is important to see whether the results would match those done on graduate student and heir faculty. The information would also be used to support the use of Biglans model in these types of research. The authors recommendation that institutions should consider their use of one size fits all type of library services is also justified. The data shows significant differences among disciplines in their use of library services for informational purposes, hence institutions can review how to adapt their services to the students patterns.

As an exploratory study that sought to determine the difference and not explains any causal relationship, the study does not have many internal and external validity factors. However, the study has external validity as it is generalizable. However, its generalizability does not statistical, but analytical. The data was sourced from institutions where there are different types of students; hence the findings can be replicable. Internal validity factors such as history, maturation, testing instrumentation, statistical regression, selection, and research mortality do not have a significant effect on this study as the author did not have control on the data, but only n the sampling.

6. Overall conclusion

Although case studies have numerous challenges based on their nature, this study was carried out well and the results can be used by other researchers. However, any researchers using this document should be aware of the limitation it had.