Session Four: Annotated Bibliography


Annotated Bibliography

Chahino, M. (2011, January 1). An Exploration of Student Personality Type and Success in Online Classes. ProQuest LLC. Retrieved from:

In An Exploration of Student Personality Type and Success in Online Classes, Dr. Michael Chahino of the Department of Educational Technology at Northern Illinois University sets out to assess whether personality traits are a mitigating factor in predicting student success in online community college students. The study revealed that personality was not a factor, however, demographic characteristics do play a role in predicting success. Furthermore, the study concluded that colleges and universities should not employ the same strategies for reducing attrition of online students as they would for traditional students, because these tactics are not successful. Online students do not have the same social interaction or connection to student services as online students would; therefore, colleges need to look at other ways to improve retention of online students. (Chahino, 2011)

According to the study, demographic characteristics seems to be an essential criteria for best predicting student success in online courses, and colleges should use this information for supporting online retention. Older working professionals with clear academic goals for professional growth are statistically more successful in online classes. Even with ideal characteristics, online classes face higher attrition rates. Ultimately the study concluded that colleges would benefit from implementing student success predictive measures because it would allow for better college planning and student guidance in course planning and student services. (Chahino, 2011)

In this study fifty community college level students were interviewed. Half of the students had been successful in the class and half had either dropped out or failed.   The purpose of the interview was to isolate personality traits and attempt to connect these traits in predicting success (Chahino, 2011) .   Because of the small size of the study and the lack of external factors (number of previously successful online completions, tech ability, overall students success, etc.), the study seems inadequate.

The key point made in this study is the recommendation that colleges should be researching ways to improve success and retention of online learners. “The shortcomings in predicting student success in online learning suggest that the methods used to assess student performance are inadequate” (Chahino, 2011, p. 6).

Like my own college, I would surmise that most colleges have not developed student success plans aimed specifically at online students. While the study in this article does not prove prediction measures, it does validate the need for schools to do more to improve online retention and success. I do not recommend this article.

Hukle, D. (2009, January 1). An Evaluation of Readiness Factors

for Online Education. ProQuest LLC. Retrieved from:

      In this dissertation, Hukle examined readiness factors in determining student success in online courses. 250 online students at Itamwmba community college responded to a survey called the Readiness for Education at a Distance Indicator (READI). READI surveyed “variables of individual attributes, technical competency (computer and internet), technical knowledge, reading comprehension, typing speed and proficiency, and learning styles…Additionally, institutional variables included in the evaluation were ACT score, online courses completed, total semester hours completed, and cumulative grade point average” (Hukle, 2009, p. 6). The study seems to have gathered a thorough base of information that would effect outcomes.

The results of the study found three common traits in students with successful students: individual attributes (undefined), high reading comprehension (confirmed with ACT scores), and logical learning style (self-identified through learning style assessment) (Hukle, 2009). Had the study elaborated on defining individual attributes, those findings would have been more significant.

Hukle makes the following recommendations:

  • Colleges should establish admissions requirements for distance education
  • Colleges must set best practices for online teaching by-
  • Educating students on the expectations and differences of online learning
  • Informing students of technology and online access requirements
  • Connect students with Library and Student Services support

This study makes some recommendations that would benefit CA Community colleges. While Title V prevents California community colleges from creating an admissions policy that would limit equal access, schools could do more to inform students on what skills and actions result in most likely success in online courses. I recommend this article.

Johnson, J.  (2013, Sept.).  The Use of E-Learning Tools for

Improving Hispanic Students’ Academic Performance.  Journal of Online Learning and Teaching, 9(3).  Retrieved from:

This study developed out of Professor Johnson’s concern that the Department of Education has shown a steady growth in the US Hispanic population and yet this minority group has remained in the bottom percentile in grade point averages, retention, and graduation rates in college minority students. The study was conducted on University students in a Hispanic Serving Institute (University of Texas). The purpose of the study was to examine the impact that technology acceptance had on performance in online classes as well as face to face classes that utilized computer based instruction.

Johnson’s found that “computer self-efficacy, ability to work independently, and time management” were significant success predictors for Hispanic students (2013, p. 1). Johnson’s premise is that online courses require students be more self reliant in the learning process; therefore, the ability to work independently and utilize strong time management skills has a positive affect on online learning.   The study reviewed 269 Hispanic students, all of whom had completed a minimum of sixty units with a grade point average of 2.5 or better. Students responded to a detailed survey pre and post online courses, as well as participated in interviews during the process. The strongest suggestion of success was time management skills, but linked to this was a relationship to older students who also worked full time. A noteworthy citation from Padron, 2002 comments on e-learning and second language learners:

E-learning tools provide a medium for students with limited English proficiency to enhance their process of English language assimilation by having asynchronous participation because videos and visual presentations with sound and animation facilitate auditory skills, while digitized books present linking possibilities tied to definitions and pronunciation help. (As cited in Johnson, 2013).

I believe the key to this recommendation for English learners is the attention to asynchronous participation since it allows students the extra time to review information multiple times before responding.

The study concludes that Hispanic students greatly benefit from online teaching tools. What is totally unclear from this study is how being Hispanic directly impacts any of the traits that support student success? Of the recommended successful online learners, these characteristics could be any student from any cultural. Overall, I don’t see how this study is of use for anyone wanting to focus on Hispanic students. I do not recommend this article.

Kaupp, R. (2012). Online Penalty: The Impact of Online

Instruction on the Latino- White Achievement Gap. Journal Of Applied Research In The Community College, 19(2), 8-16. Retrieved from:

     This study exams the gap between the high number of Hispanic students represented in community colleges compared with the low completion and transfer rates. The study reviews CA community college success and completion rates and finds an even larger disparity in the number of Hispanic students who successfully complete online classes. According to the study, Hispanic students are twice as likely to drop out of online classes as face to face courses. They are also 9% less likely to be successful in online classes as Caucasian students, and they earn 2/10ths of a grade point average lower (Kaupp, 2012). Professor Kaupp of Cabrillo college attempts to answer the question- how does enrollment in online classes impact the success of Hispanic students?

Through a series of interviews with Latino students (numbers not stated), Kaupp establishes two key cultural factors that seem to indicate a negative impact on Hispanic online student success. The biggest issue identified relates to the cultural importance placed on Hispanic students establishing a strong student-instructor relationship. This resonated with me because anecdotally my colleagues and I can attest that my students (largely Hispanic immigrant or 1.5 generation) are far more likely to visit me during office hours than the Caucasian students. Secondly, the study suggests that social interaction of crating learning communities and establishing student relationships is another pivotal point in success of Hispanic students.

While the article does show cultural connections for establishing why Hispanic students might struggle in online classes, it lacks in providing any recommendations. Practically speaking, both the student/instructor and student/student relationships can be established in online classes. Agreed that most online courses do not lend themselves to directly building strong connections, there are certainly activities, apps, and assignments that could foster stronger online learning communities and faculty/student interaction. I recommend this article.

Menager-Beeley, R. (2001). Student Success in Web Based

Distance Learning:  Measuring Motivation To Identify at Risk Students and Improve Retention in Online Classes.

     This study looks at student motivation and drop out behavior. Professor and Author Menager-Beeley asserts that there is a strong correlation between student success and motivation, in addition, the author believes at-risk students likely to drop can be identified within the first week of online classes. According to Menager-Beeley,

Gender, ethnicity, subject, level of prior English classes, or ESL (English as a Second Language), did not influence persistence in the class. It was found that students with low task values, low prior grades in English, and older students (over 28 years) may be more likely to drop out of a class that is completely Web-based, and that this can be reliably measured (2001).

     The study survey one hundred and fifty online Social Science and Psychology students, however, only fifty-nine students responded to the first week emailed survey. In that survey, students were asked to rate “three specific aspects of Task Values: Interest, Importance, and Utility” (Menager-Beeley, 2001, p. 3). Given the low participation and self-response with no interviewing, this study seems statistically irrelevant.

There seem to be several flaws in the line of reasoning of this study. For practical purposes, the strategies for identifying at-risk students need to happen prior to enrollment because once a student enrolls, it’s too late. While I understand that the study is intended to educate faculty on identifying at-risk students in their own colleges, for my research purposes, I am more interested in what the institutions and faculty can do prior to classes starting. Also concerning is that these findings seem to contradict numerous studies that have found that in fact older students are more likely to be successful in online class. I would not recommend this article.


Cassens, T. (2010, January 1). Comparing the Effectiveness of

Online and Face-to-Face Classes among California Community College Students. ProQuest LLC. Retrieved from:

Chahino, M. (2011, January 1). An Exploration of Student

Personality Type and Success in Online Classes. ProQuest LLC. Retrieved from:

Evaluating Online Courses. (N.D.) Retrieved from Michigan State

University Online Evaluation:

Harrell, I., & Bower, B. L. (2011). Student Characteristics that

Predict Persistence in Community College Online Courses. American Journal Of Distance Education, 25(3), 178-191. Retrieved from:

Hukle, D. (2009, January 1). An Evaluation of Readiness Factors

for Online Education. ProQuest LLC. Retrieved from:

Johnson, J.  (2013, Sept.).  The Use of E-Learning Tools for

Improving HispanicStudents’ Academic Performance.  Journal of Online Learning andTeaching, 9(3).  Retrieved from:

Li, G. (2012). Literacy Engagement through Online and Offline

Communities outside School: English Language Learners’ Development as Readers and Writers. Theory Into Practice, 51(4), 312-318. Retrieved from:

Kaupp, R. (2012). Online Penalty: The Impact of Online

Instruction on the Latino- White Achievement Gap. Journal Of Applied Research In The Community College, 19(2), 8-16. Retrieved from:

Kegelman, N. (2011, January 1). Online Courses at a Community

College: A Study of Student Characteristics. ProQuest LLC. Retrieved from:

Menager-Beeley, R. (2001). Student Success in Web Based

Distance Learning: Measuring Motivation To Identify at Risk Students and Improve Retention in Online Classes.

Muse Jr., H. E. (2003). The Web-based community college

student: An examination of factors that lead to success and risk. Internet & Higher Education, 6(3), 241. doi:10.1016/S1096-7516(03)00044-7

Park, H., & Kim, D. (2011). Reading-Strategy Use by English as

a Second Language Learners in Online Reading Tasks. Computers & Education, 57(3), 2156-2166. Retrieved from:

Phillip, A. (2011). The Online Equation. Diverse: Issues In Higher

Education28(3), 20.

Quality Online Course Initiative Rubric & Checklist. (2010).

Retrieved from University Illinois:

Ramezani, K. (2010, January 1). The Implications of Using

Online Classes with At-Risk Students in an Alternative School Setting. ProQuest LLC. Retrieved from:

Rey, J. (2010, January 1). The Effects of Online Courses for

Student Success in Basic Skills Mathematics Classes at California Community Colleges. ProQuest LLC. Retrieved from:

Rubric for Online Instruction. (20140. Retrieved from CSUC:

Shank, P. (2007). (Not) Making it Hard(er) to Learn, Part 1. Online

Classroom, 4-8.  Retrieved from:

Slate, J. R., Manuel, M., & Brinson, K. H., Jr. (2002). The “digital

divide”: Hispanic college students’ views of educational uses of the Internet.  Assessment & Evaluation in Higher Education, 27(1), 75-93. doi:10.1080/02602930120105081

Taylor, V. (2003, May 12). Excellence in Online Teaching and

Strategy. Retrieved from: De’Anza College Rubric-$146

Wilcox, B. L., & Wojnar, L. C. (2000). Designing a “Best Practice”

Online Course. Retrieved from:

5 thoughts on “Session Four: Annotated Bibliography

  1. Hi Christen,
    I agree that Dr. Newberry had great tips and I loved your apps.
    I would like to speak to the rapid feedback issue: I have always known that immediate/or as immediate as possible is an important component in learning. It is difficult to keep up when you see over 200 students or more per day in a f2f class. In primary grades, many teachers walk around and make corrections and give feedback as they go. Later, it is harder to do that. That is where I think the assignments need to be smaller, or in increments so the student knows if they are off track before it is too late. I have seen many teachers assign a research report, give it a due date, and expect the student to turn it in. Grading the reports as you go saves the teacher time and gives the student instruction and feedback. So to me, it is good teaching practice at any level.


  2. Christen,

    Your blog entries are always a joy to read! They are well thought out and presented. Plus they are always grammatically correct.

    Your current postings reminded me of a conversation I had with a colleague at SBBCollege. Specifically, I am in the midst of updating a f2f course called Professional Development: the course teaches students the “how to’s” needed to make a student marketable upon graduation (e.g., resume writing, interviewing, creating elevator speeches).

    There is also an on-line version of the class that contains the same content without any f2f contact. While a blended version might work, The conversation has been about how do you assess interpersonal behaviors without a second person.

    Given some of this week’s assignments, I am gaining some thoughts on how to use skype, videos and perhaps video conferencing to overcome some of the limitations.

    I also found your discussion on how Hispanic students could be more successful with asynchronous on-line learning. The article raises several issues that need to be explored in greater detail. For example in an increasingly diverse and global multilingual society, where may of the involved audiences where English is a second language.


    • Thanks for the kind words. I got a good laugh over the complement of my grammar. I’m actually really finding the assignments in this class interesting, so it makes it easy to write.
      I teach the professional development skills you mentioned in a f2f class that includes writing answers to the top 25 most common interview questions followed by a job interview that I conduct for a position they have “applied for” based on a real job ad. I think it is the most effective lesson I teach in my whole program.
      Doing the interpersonal skills online poses some challenges. Having interviewed teachers via Skype, I can say that no one does well in that format- no eye contact. That would be tough to grade. I would try to think about how to assess interpersonal skills via written communication (email/discussion board/text) maybe???
      If you ever want to see the materials I use in my class, email me.


  3. Greetings Christen,
    I really like the following article on :
    Hukle, D. (2009, January 1). An Evaluation of Readiness Factors

    because it emphasizes that students must be connected to additional support systems like library and student support which will enhance learning opportunities.

    For instance, support from libraries in which they provide “custom web pages with resources that are relevant to individual courses” (Moore, 2012, p. 95). Practices like this specifically tailored to course content will ensure access to various resources, students’ implementation of technological tools in creating instructional products , and success in completing their program.
    Moore, J. C. (2012). A Synthesis of Sloan-C Effective Practices, December 2011. Journal of Asynchronous Learning Networks, 16(1), 91–115.


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