1. Introduction

Globally, education is viewed as a key component which forms the basis of development in any economy (Theodore, 2013). Parents and teachers have always put pressure on school-going children to excel in their academic work. How to work hard in school has continued to be an area of interest for students as well as many stakeholders in education. First year students experience challenges that include autonomy, social adjustment, peer compatibility, and academic pressure (Wangeri, Kimani, and Mutweleli, 2012). Those that are not able to manage the transition and adapt to the new environment at the university often experience adjustment problems which might even affect their academic work. Learning has been observed as a cognitive process that is dependent on meta-cognitive behaviors such as attending, focusing, questioning, comparing, and contrasting, that are personally controlled or managed by the learner (Long, 2011). According to Knowles (2008) self-directed learning is a process in which individuals take the initiative in designing learning experiences, diagnosing needs, locating resources, and evaluating learning. Similarly, a definition for the readiness for learning is provided by Guglielmino (2009) stating that it consists of a complex of attitudes, values, and abilities.

Majority of students drop out of university during or after their first year of study (University World News, 2008). The annual survey of the American College Testing organization (ACT) among 500 institutions in the USA, indicated a dropout rate ranging from 31.8% to 47.2% among undergraduate students (ACT, 2003). Similarly, the graduation rates in the USA for the last twenty years have remained relatively stable, ranging from a high of 54.6% to a low of 50.9% (ACT, 2003). In the United Kingdom, 25% of students at university did not complete their degree program in 2002 (University World News, 2008). As a further example of international trends, in Australia, according to Health Gilmore Higher Education (HGHE) (2009), 20% of first year students drop out of university before the end of the first academic year. In South Africa, data shows that 50% of undergraduate students enrolled in higher education institutions in South Africa drop out, with about 30% dropping out in their first year (Department of Education, 2005). A more recent study by the Human Science Research Council (HSRC) found that 40% of students drop out of university in their first year (University World News, 2007).

The dropout of students from university, as well as students taking longer to complete their studies, has certain consequences for the student, university and the state. A university education provides students with a higher overall income, an improvement in living standards, and a degree of recognition for their achievements compared to students with only a high school education. In turn, a student graduating from university will provide the state with higher tax revenues and a return of the investments placed in the students through government loans, bursaries and funds. Low graduation of students, as well as high dropout of students not only negatively affects the university budget but also lowers public conviction about the quality and standard of education offered at university (Braxton, Hirschy, and McClendon, 2004). For students to be competitive in the global market place, they have to be well educated, trained and skilled. Consequently, for a country to be successful and develop economically and socially, highly qualified and educated students are a prerequisite. University graduates are essential in order to address the high level skills shortage in the country (Scott et al., 2007), affecting economic development and growth.

The type of goals a person sets can have a major impact on one’s long term performance. Performance goals are the most basic goals, they are directly correlated to an outcome. These goals can be great in the short term, but they also have some downsides. Performance goals by their nature are rather shallow; if you had to cheat, at least you still hit your goal. Performance goals also tend to undermine long-term performance. If you hit your initial goal, you become less motivated to continue towards excellence (after all you hit your goal). And if you do not hit your initial goal, you become discouraged and de-motivated because your self-worth is based on external inputs (Hullman and Senko, 2010).

Literature on performance aproach goals and learnming outcomes have been documented. In USA, Senko, Durik, Patel, Lovejoy, and Valentiner (2013) conducted an examination on the effects of university students’ achievement goals on performance under low versus high challenge conditions. The results found that performance-approach goals facilitated high achievement in the high challenge condition but not in the low challenge condition. A study in Belgium by Vansteenkiste, Smeets, Soenens, Len, Matos and DeciIn (2010) used self-determination theory to examine whether autonomous and controlled regulation of performance-approach (PAp) goals would differentially predict educational outcomes and add to the variance explained by the goal strength. Finally, path modelling indicated that autonomous and controlled regulations of PAp goals (but not PAp goals themselves) accounted for nearly all of the relation between the types of perfectionism and learning outcomes. In U.S.A Ordene Edwards (2014) found that normative performance approach goal had a significant positive effect on self-efficacy and interest, but had no effect on fear of failure. In contrast, competence demonstration performance approach goal had a significant positive effect on fear of failure, but was not related to self-efficacy and interest. In Turkey, Tercanlioglu, and Demiröz (2015) did a study whose aim was to investigate qualitatively the role of goal orientation in reading comprehension both in native (L1) and second or foreign languages (L2), and the reading strategy use in L1 and L2 of the Turkish advanced students of an English Language Teaching (ELT) Department in order to understand the pedagogical aspects of reading. The data of the study evidenced that mastery goal oriented, and high mastery and low performance-approach participants use more strategies than the performance approach (except for one) and work-avoidant participants. Jury, Mickael, Quiamzade, Alain, Darmon, Celine, Mugny and Gabriel (2018) did a study on Higher and Lower Status Individuals Performance goals and the role of hierarchy stability. The results of both studies supported that the difference between higher and lower status individuals in terms of performance-based goal orientation only appeared in stable hierarchical systems, sustaining a view of performance-based goals as dynamic processes resulting from the position one occupies in a hierarchical system.

Crouzeviall and Butera (2016) in Switzerland did a study where performance-approach goals were found to be positive predictors of test performance. The interaction appeared only among low achievers for whom the pursuit of performance-approach goals predicted greater performance-but only when the test had been scheduled. Conversely, high achievers appeared to have adopted a regular and steady process of course content learning whatever their normative goal endorsement. In Turkey, Nur (2016), investigated perceived mastery versus competitive learning environment relates to better learning strategies. Hierarchical regression analyses revealed that perceived mastery-approach goal structures predicted positively mastery-approach goals, which in turn predicted positively challenge-seeking and negatively challenge-avoidance. Also, perceived performance goal structures predicted positively performance-approach goals and performance-avoidance goals with the latter being in turn negative predictors of challenge-seeking and positive predictors of challenge-avoidance. Performance-approach goals were positive predictors of grades, even after controlling for mid-year grades. In Turkey, Sakiz (2011), explored the associations among achievement approach goal orientations, academic self-efficacy beliefs, and academic help seeking behaviors of Turkish college students. Performance approach goal orientation, on the other hand, was not significantly related to academic self-efficacy beliefs but significantly negatively associated with students’ academic help seeking behaviors. Overall, the structural model explained 31% of the variance in academic self-efficacy beliefs and 39% of the variance in academic help seeking behaviors of college students.

In the USA, Matuga (2009) found out that students appeared to enter the online university course with a performance goal orientation, concerned with getting a good grade. Moreover the study showed that majority (88%) of the students received high scores (A’s and B’s) for the final year, and only a few did not. Higher education institutions in South Africa report dismal student graduation rates as a norm. A survey between 2002-2003 reveals that the country has the highest number of higher education students in sub-Saharan Africa but that less than two students in every ten actually graduate (Page, Loots, and Toit, 2005). A study on some factors which contribute to poor academic achievement among undergraduate students found out that most of them are affected by external factors as compared to their internal locus of control (Fakude, 2012).

In Ethiopia, a study reported that the rate of enrollment in physics undergraduate programs are those whose mean scores in Ethiopian National Higher Education Entrance Examination is lowest. Explanations given for the low enrollment rate are inadequate pre-university preparation which results to lack of learning readiness, and also weak mathematics background (Semela, 2010). In Kenya, some studies have shown that majority of the students do not have access to support services like deans of students’ mentoring programs, wellness etc. The students have low adjustment to academic programs (Wangeri, Kimani, and Mutweleli, 2012). In Kenya, Okinda (2014) reported a low readiness level which suggested that internal environment may hinder efforts to adopt e-learning as a mode of deliver.

All universities take fresh students through an elaborate orientation programme meant, among other things, to assist students adjust to the new social and academic environments in the university context. Specifically, the orientation process is meant to make them ready to learn. In this context inappropriate learning readiness among first year students in universities due to adjustment challenges-since first year is a transition period-may result to loss of many rewarding opportunities both for the individual learner and for the society. The student may miss a job opportunity due to failure in examinations (which may delay completion) which may lead to dropping out of college or repeating a course and in the long run, the society may not have enough skilled human capital needed to meet the demands for wealth production and overall socio-economic development at the time anticipated. Thus, there was need to study factors that are associated with learning readiness. Since there is need of adjustment among first year university students which facilitates their learning readiness, it has prompted universities to organize the orientation programmes for fresh students. All universities take fresh students through an elaborate orientation programme meant, among other things, to assist students adjust to the new social and academic environments in the university context. It is meant to make them ready to learn. First year is a transition period-inappropriate learning readiness among first year students in universities due to adjustment challenges-may result to loss of many rewarding opportunities both for the individual learner and for the society. Thus, there is need to study factors that are associated with learning readiness. Its against this background that the researcher investigated how performance-approach goalsimpacts learning readiness among first year university students.

2. Research Methodology

The study employed a mixed methods approach, this involved the collection, analysis and integration of both quantitative and qualitative research methods within a single research study in order to answer research questions. Specifically, the embedded mixed method design was employed whose purpose was to collect both quantitative and qualitative data simultaneosly, but to have one form of data play a supportive role to the other form. In this study, qualitative data was collected to corroborate quantitative data (Creswell, 2014). The target population was 12,000 first year university students from six public universities in the lake region of Kenya, 122 lecturers, 6 deans of students, 6 university counsellors. Western Kenya has a total of six public universities. Out of these, three were sampled for the study. The sample size consisted of 372 first year students, 20 lecturers, 3 deans of students and 3 university counsellors. In addition to student questionnaires, 23 interviews were conducted, transcribed and analyzed. The study employed questionnaires, and interview schedules to gather information addressing research objectives. The Goal Questionnaire for Students (GQS, [Elliot and Murayama, 2008]) was modified to measure mastery-approach goals while the Learning Readiness Questionnaire (LRQ) was modified to measure learning readiness of first year university students. The study also employed Interview Schedules.

Validity of research instruments in the present study was through, face, construct and content validities of the questionnaires, interview schedules and document analysis was determined by presenting and discussing the various items in research instruments with two experts in the school of Education of Jaramogi Oginga Odinga University of Science and Technology (JOOUST) who were actually the PhD thesis supervisors. The supervisors were able to provide their views on the relevance, clarity and applicability of the questionnaire scales, interview schedule guides and document analysis guide. Their suggestions, together with the findings from the pilot study were used to modify the items in the research instruments. This ensured that the test items were clear, relevant and well organized. Triangulation approach was further adopted to ensure the validity of the research instruments where data from multiple techniques validate each other (Mugenda and Mugenda, 2012). The study used multiple methods of data collection through interviews, and questionnaires. This enabled areas that may might have been overlooked by one method to be strengthened and checked by the other method of data collection. Reliability of the instruments was tested during the piloting stage. Piloting was conducted in 1 university in Western Kenya region of which 10 Students, 8 Lecturers, 1 Dean of students, and 1 University Counsellor were selected randomly for piloting. The researcher used internal consistency method to determine the reliability of the instruments. This was done using Cronbach’s alpha. According to (Oso and Onen, 2014), a questionnaire has good internal consistency if the Cronbach alpha coefficient of a scale is above 0.7. In this study internal consistency reliability of the instruments was obtained by computing Cronbach’s alpha (α) using SPSS Version 23.

3. Findings and Discussion

The research findings were presented on the basis of the study objectives and hypotheses. The quantitative data were analyzed using both descriptive and inferential statistics. The descriptive statistics was used to describe and summarize the data in form of tables, frequencies, percentages, means and standard deviations. The inferential statistics was used to help make inferences and draw conclusions. Statistical tests, Pearson product-moment of correlation and regression analysis were used to investigate the relationship between the variables. All tests of significance were computed at α = 0.05.The Statistical Package for Social Sciences (SPSS) version 22 was used to analyze the data. For the qualitative data a thematic analysis approach was used.

Hypothesis Testing:

To investigate whether there was any statistical significant relationship between mastery-approach goals and learning readiness among first year undergraduate university students, the null hypothesis was tested as follows:

H₀1: There is no statistically significant relationship between performance-approach goals and learning readiness among first year undergraduate university students.

To do this, a Pearson Product Moment Correlation Coefficient was computed. Table 1 shows the correlation analysis results in SPSS output.

Table 1. Relationship between Performance-Approach Goal and Readiness to Learning

Table 1 has revealed that there was statistically significant positive, moderate, correlation (r=.665, n=324, p<.05) between performance-approach goal orientation and learning readiness, with high performance-approach goal orientation resulting into improved learning readiness among the first year university undergraduate students and vice-versa. Given that the relationship was statistically significant (p< .05), the hypothesis that, “there is no statistically significant relationship between performance-approach goals and learning readiness among first year undergraduate university students” was rejected. It was therefore concluded that there is statistically significant positive relationship between performance-approach goals and learning readiness among first year undergraduate university students. This is consistent with Nur (2016) study findings which revealed that performance approach goals were positive predictors of grades, even after controlling for mid-year grades.

The study further sought to establish the relationship between performance-approach goals and individual aspects of learning readiness in four aspects; self-management study strategies, desire for learning, self-control and perseverance, as indicated in Table 2.

Table 2. Correlation between Performance-Approach and Individual aspects of Learning Readiness

It evident from Table 2 that all the aspects of learning readiness were statistically significantly (p < .05) positively related to performance-approach goal orientation among the first year university undergraduate students. All the variables, except perseverance, had above r=.5, which though was significant had the least statistically significant relationship between performance-approach, as reflected by a p-value <.05 at r=.357. The findings are inconsistent with Crouzeviall and Butera (2016) in Switzerland where performance-approach goals were found to be positive predictors of test performance.

H₀2: There is no statistically significant extent to which performance-approach goals impacts learning readiness among first year undergraduate university students.

To estimate the level of influence of Performance-approach goals on overall learning readiness, a coefficient of determination was worked out using a regression analysis whose results were as shown in table 3.

Table 3. Model Summary on Regression Analysis of Influence of Performance-Approach Goal Orientation on Learning Readiness

From the model, it is evident that performance-approach goal orientation accounted for only 44.3% (coefficient R²=.443) of the variation in learning readiness among the first year university students.The findings are consistent with Senko, Durik, Patel, Lovejoy, and Valentiner (2013) study in U.S.A which found out that performance-approach goals facilitated high achievement in the high challenge condition but not in the low challenge condition.

During the interviews with the first year university students, some students expressed that their concern was about passing examinations and completion of their Bachelors degree which make them work hard. This can be regarded as a performance-approach goal orientation. Among the identifying key features of this goal orientation are attention to the performance of peers, competition and attempts to show their abilities to their instructors. In line with this view, two first year university students observed:

I am highly concerned about grades of my classmates and want to outperform them. This is also the case with writing my assignments. (Student, 11)

When am writing my take away CATs or any assignment, I always think about First year is a different period from the rest, students are anxious, they can even ask the highest score of a CAT for example, eager even to know the person, but as they move to year two and subsequent years, it starts disappearing, they are never bothered on who gets highest score. (Lecturer, 09)

In the above excerpts, the student is concerned about other’s views about his/her work and then because this concern tries to improve his/her work. This is a new dynamic as far as student motivation to work hard is concerned yet an important one; the general perception is that students influence their peers to bad behaviour. This is inconsistent with Chiu and Chow (2015) whose findings showed that classmates family factors were more strongly related to a student reading achievement than were classmates.

4. Conclusions and Recommendations

Based on the current study findings, it can be concluded that, the university has a big role in facilitating successful transition of first year university students. The Deans of students, Lecturers, University counsellors all need to guide the first years accordingly so that they are don’t fall victims of threats which makes it hard for them to adjust to university life hence low learning readiness. The study established that many of the students generally have relatively low performance-approach orientation. The findings of this study reveal that considerable number of students accept that their orientation is not performance approach. The study shows that a few students engage in rigorous class work to pass exams so as to outperform others.