The issue of working with students who are on academic probation is certainly not a new one, and the challenge comes with many obstacles. Although many of the challenges are driven by students and their particular skill sets or demeanor, some of those challenges can be driven by the institutions. There are several key issues identified in the literature relating to factors of underperforming students or those earning a low GPA. As described by Cruise (2002), one of the reasons students earn a low GPA is, “Sometimes students fail courses because they are not interested in what is being taught” (p. 2). Students may not care for the content being taught, and they begin to loose motivation and interest. The idea of this need for motivation is backed up by Balduf (2009), who wrote about students’ lack of motivation and goals, “Both motivation and goal valuation were likely factors in determining why students were not successful” (p. 278). Another reason for a low GPA is identified by Engstrom & Tinto (2008) as, “Low economic students are more likely to begin higher education academically under-prepared than those from affluent backgrounds” (p. 47). The theme of lower economic status is echoed in several other reports, and the common thread is that these students may be at a distinct disadvantage and a higher probability of being on academic probation (Engstrom & Tinto, 2008; Cruise, 2009).
information literacy services (that is, Ask A Librarian/reference and library instruction). A greater number of students used information literacy services than materials services, but those students who used materials services tended to use them more times than did students who used information literacy services. The average transaction count for library instruction sessions (1.3) suggests there is little overlap among students who attend these sessions. The low usage of interlibrary loan and request delivery services may indicate students lack patience when it comes to obtaining library sources. Rather than searching for the best source, students may accept the information they find as satisfactory and then stop searching, perhaps because the system is difficult for them to use. 22 Students may make do with items immediately available either online—via the library or not—or within the physical library, thereby contributing to less frequent use of materials request services.
The empirical assessments of the traditional teaching approach of lecturing in the undergraduate classroom indicate its ineffectiveness in the learning process. This traditional pedagogy has been identified as one of the major reasons adversely impacting student engagement and motivation, especially in the science, technology, engineering and mathematics (STEM) fields. Re- search on learning provides strong evidence that active-learning can have a positive impact on student learning outcomes. The biggest challenge with in- corporating active-learning strategies in the classroom is the time constraint of the traditional class period. One of the approaches that is finding increas- ing acceptance among educators is the use of the flipped classroom. This pa- per shares details of the impact of active-learning on academic achievement of students from groups underrepresented in STEM in introductory mathe- matics and aerospace engineering courses. The results indicated that the per- formance of students who took the courses with the active learning improved.
In any case, it is essential to avoid lack of concern and rather take up cognizant and even minded estimates now in order to block the marvel from further intensifying understudies' composition aptitudes. So the theory concerned is endorsed and it's reasonable the unnecessary utilization of messaging influence understudies composed aptitudes. All endeavors must, in this way, be made to enable understudies to compose great English whether on telephone on paper and casual work. The ongoing computing and smartphone advancement has negative impact on student’s academic writing performance and requires serious policies to stop students to excessive use of SMS during their study time and also in assignments and papers. Decisions have to be taken carefully. Such work would be valuable for educational policies. The purpose of this paper is not to against advance technology like social media, smartphones, and internet. Texting can hurt students writing and grammar. Text because they are used toting was made easier for the students. Students can accidentally put slang language in their formal writings without realizing it. Students expect someone to fix their misspellings in class because they are used to their autocorrect doing it on their phones.
Problem: The expectation of the current nurse workforce is to deliver safe quality care while meeting the demands of an ever-changing healthcare system. More nurses are needed to combat the ongoing nursing shortage, as Baby Boomers reach retirement and the need for health care continues to rise. The healthcare industry has a vested interest in schools of nursing graduation rates as they impact the needed supply of nurses to fill vacant positions. Multiple variables collectively influence student success in a nursing program. Many students do not realize the rigor of a nursing curriculum until they are in the midst of it. Attrition rates, at all degree levels, are high across the United States. It is imperative that nursing programs take a proactive approach and utilize best practices to assist qualified students to succeed academically.
11 Zilla Parishad High schools (Two are girls’ schools and others are coeducation) from Guntur rural villages and Seven municipal High schools were selected for the study. 8 th Classstudents were chosen as subjects. A total of 1510 students was participated and out of them 805 students were studying in rural schools and 705 in urban schools (Table 1). The response was taken for six questions they are;
This study was aimed to evaluate the learning styles of education faculty students and to determine the effect of their success and relationship between their learning styles and academicsuccess. The popula- tion of this study is comprised of the students of Education Faculty in 19 May University and the sample includes 140: 68 art, 72 pre-school teacher department students. Depending on the results obtained from pre-test, it was aimed to improve students’ knowledge and skills in studying. There was a significant dif- ference between the scores of pre- and post-tests. The significant relationship between the scores of post-test and the student success revealed that they learned how to study effectively. The validity and re- liability of the test were determined by considering the Cronbach alpha coefficients for each and all of the items. The study has found statistically significant differences between the results of the first and final applications of the subtests on learning styles and academicsuccess; those subtests covered the items as learning, planned study, effective reading, listening, writing, note taking, using the library, getting pre- pared for and taking exams, class participation and motivation.
Factor analysis was performed to ensure valid measurement for the influence of work experience on academic learning variables, based on students’ perceptions with no specified a priori restrictions. Exploratory factor analysis (EFA) is best applied for scale development and to evaluate the pattern of relationships among items (Tabachnick & Fidell, 2007). Furthermore, EFA helps to minimize scale overlapping and improve internal consistency. Initial factor analysis was conducted using principal component extraction with varimax rotation to estimate the factorability of the correlation matrices, the absence of multicollinearity and singularity, the Kaiser measures of sampling adequacy, the number of factors, and the inter-factor correlations. The maximum likelihood extraction method was used for further analysis, because it provides a stricter test of relationship among variables, which happen because it requires a positive definite covariance matrix (Tabachnick & Fidell, 2007).
benefit certain areas and populations in education. Specific coaching strategies can be provided to target certain student populations such as learning disabilities (attention deficient disorder, processing disorders ), autism, english as a second language, and academically gifted. Resources such as special educational teacher and specialized educational plans are important to be included in the process to measure effectiveness of coaching. In additional to researching a bigger variety of student needs, sample sizes need to be taken in consideration. As this study measures qualitative data, a smaller sample size was appropriate. However, for any future quantitative studies, a bigger sample size would be needed. Additionally, studies targeting the impact of coaching on specific factors that impact learning (i.e., age groups, learning disabilities, socio-economic diversity) need future exploration. In adolescence, students are developmentally diverse. This diversity must be analyzed yet respected as
The academicsuccess of a student dependents on several factors. For ex. Level of concentration in the classroom, recall, friends nature, health problems, handwriting, fears and phobias, etc. Teachers shall record these factors and shall guide the students. Otherwise, these factors hinder the progress of a student. The present study was aimed at studying observation of these factors in 9 th class
Further, the educational gaps of those in Appalachia are staggering with ACT scores well below state and national levels (Kentucky Department of Education, 2011). Studies have shown that rural environments impact lives and the life outcomes of the rural dwellers (Brown, Copeland, Costello, Erkanli, & Worthman, 2009). Additionally, negative stereotypes depicting the people of the area abound impacting how the people of Appalachia come to view themselves or internalize how others see them (Wallace & Diekroger, 2000;& Winter, 2013). The misconception that rural dwellers do not value education runs rampant in academia further adding to the bleak view of rural students (Howley, 2009; Wallace & Diekroger, 2010). This ideology must be challenged to change the way the outside world sees those from rural Appalachia. Further, this view is ironic considering that 57% of community colleges serve a rural population (Cejda, 2010). Examples of those rural Appalachians who triumph over the stereotypical view of rural dwellers often held by those outside the area can challenge such a minimizing external view.
2007). A study done with 1,639 Asian immigrants looked at language preference related to their health care interactions. The study found that only 11.3% of participants think only in English all the time (Gee, Walsemann, & Takeuchi, 2010). The authors found a positive association and years of education with the use of English language preference. Stevenson (2015) conducted a qualitative study with 15 bilingual students, 80% of the students had an advanced level of English proficiency and preferred to use English. The author found that participants used English 72% of the time during class sessions; due to the fact, their teacher interacted mostly in English. Also, the author revealed that students were aware that other students preferred speaking English as a necessity of improving English to increase their academicsuccess and further their educational opportunities. The bilingual students were aware of the importance of learning English in order to feel comfortable interacting with others. Language preference can have a positive impact on students’ bilingualism and also other educational efforts. Language Experience, Bilingualism, and AcademicSuccess
First-generation college student status. The present study found that first-generation college students had decreased odds of being academically successful in corequisite courses. Thus, first-generation college students are at an academic disadvantage in both corequisite English and mathematics courses. For example, in corequisite mathematics, if all the other predictors investigated in this study were the same between two students, except one student was a first-generation college student, a non-first-generation college student’s odds of passing a corequisite mathematics course were approximately 1.38 times that of a first-generation college student. The results of the present study agreed with Houston and Xu’s (2016) findings that first-generation college student status had a negative effect on student academicsuccess in mathematics. However, the present study’s findings were not in alignment with Chen’s (2016) findings that parental education level does not seem to have an impact on earning college-level mathematics credit. In either case it would be appropriate for institutional administrators, faculty, and academic support professionals to create an environment where first-generation students can readily find the support that they need to be academically successful in corequisite courses.
An increase in student enrollments in American institutions of higher education has corresponded with an increase in online educational offerings (Walton, 2011). In turn, larger numbers of students are pursuing non-traditional doctoral degrees (Archbald, 2011). As institutions embrace online education as a means to reach and educate more students, problems of effectiveness must be addressed. The problem is that of the low retention of online students in general and its implications for non-traditional doctoral students in particular (Carr, 2000; Chyung, 2001; Stover, 2005). In comparing ground versus online programs in general, Stover (2005) asserts, "Everyone agrees that retention rates for distance education programs are lower than traditional on-campus programs” (p. 1). If this is the case, then it is important to examine factors that contribute or impact student success in online programs, not only to help students be successful but to add credibility to online programs (Stover, 2005). Further, if online attrition rates for online or non-traditional undergraduates are worse than those of their traditional counter-parts, and traditional doctoral attrition rates are near 50-60%, then non-traditional doctoral student attrition may be worse (Carr, 2000; Council of Graduate Schools in the United States, 2008; Stover, 2005).
et al. . In the study, the impact of jigsaw technique (independent variable) on academicsuccess (dependent variable) was examined. In the quantitative sub-factor of the study, an experimental research based on “pretest- posttest with control group” design was conducted. Experimental studies are those in which there are two groups; one being the experimental and the other being the control group. In such studies, after the experimental process is conducted on the experimental group, the results are compared with both groups Ekiz . Pretest- posttest with control group design is strong one that provides the researcher with high statistical power relating to testing the impact of the experimental process on the dependent variable and one that enables the interpretation of the findings within the context of reason-result relationship Büyüköztürk . In the qualitative sub-factor of the study, interviewing technique was used to collect in-depth information on the process of implementation and on the purpose of the study. The answers to the interview questions prepared based on expert opinion were subjected to content analysis and examined accordingly. It has been emphasized that the qualitative stage within the sequential explanatory design is applied for the purpose of explaining the relevant results in more detail, using an approach that focuses on explaining the findings Morgan .
There were more favorable impacts when looking at the data by subgroups. In particular, females, low SES students, low academic ability students, and high academic ability students showcased positive impacts in certain aspects of their academicsuccess. Based on these results, I pose the question: Does SBP have the strongest impact on at-risk populations despite being a program for all first-year students? Although it sounds beneficial to have a program that is broadly open to any student that wants to participate, it may have unintended consequences by compromising the benefit of the program. It is possible that a summer bridge program may be most impactful if it is for a specific population rather than all students. If this is true, this may explain some of negative findings of this study. This may also explain why there is not research on why students participate in summer bridge
For universities and students alike, graduation is a key indicator of a student’s successful academic progress. Understanding the characteristics and factors affecting students both positively and negatively on their way to graduation is imperative for a university looking to increase both retention and graduation rates. Throughout this study, entering characteristics (e.g. such as high school academic performance, residency, financial need, etc.) were considered in addition to exploring the impact of first semester student involvement on GPA, retention, and graduation. If one considers the timeline of a student, students enter the university with certain characteristics, then choose and participate (or not) in different forms of student involvement during their first semester prior to earning their first semester GPA (most commonly, during the fall semester for those who follow a typical enrollment pattern). After earning their fall GPA, students must decide whether to return to the university the following semester, the following year, and eventually, whether to continue to graduation or to leave the university. Therefore, understanding the impact of student involvement (while considering entering characteristics) on first semester GPA, first semester retention, first year retention, and graduation provides an opportunity for intervention and support.
In Table 2, results show that emotional factors such as in- teraction with the persons around (IPA) and the ability of self- regulate emotions (ASRE), can predict later academicsuccess for students in the second grade. There are almost the same re- sults within the third grade, presented in Table 3, where factors like experiences recognize and express emotions properly (ER- PEE) and the ability of self-regulate emotions (ASRE), show high relationship level with academicsuccess, while in Table 4, show no significant correlations between social-emotional de- velopment and academicsuccess.
Dei (1996a) asserts that anti-racism education “acknowledges the traditional role of the education system in producing and reproducing not only racial but also gender, sexual and class- based inequalities in society.”(p. 34). For example, Czopp (2010) found that white teachers, school sports coaches and guidance counsellors tended to ‘track’ black students towards different (and often less demanding) academic goals than white students. In this case, he proposed that this was not a result of “hostile prejudiced attitudes”(p. 495) where educators were determined to keep educational resources away from black students, but it was in order for educators to confirm their own ‘positive stereotypes’ (i.e., good at sports, more likely to find success in non-academic areas) about black students. Sperling & Vaughan (2009) might disagree – they contend that a backlash by the white American population is occurring in response to the American government allocating funds to at-risk schools which often ostensibly serve a high percentage of black and other minority students. Sperling & Vaughan argue that whites would rather maintain the status quo of allocating more educational and social resources to white students over black students. Why use anti-racism instead of multiculturalism?
The higher secondary students are having moderate level of academic stress and irrespective of sub samples of the higher secondary students are having moderate level of academic stress. Male and female students do not differ significantly in their academic stress scores. Rural and urban area students do not differ significantly in their academic stress scores. Government and private school students do not differ significantly in their academic stress scores. Science and Arts students do not differ significantly in their academic stress scores..