Pakistan Education Review

51 Research Hypothesis Ho There is no significant difference between self-reported and observational score in the teaching social-emotional teaching competence of school teachers in Islamabad Research Instruments Data was collected using two Likert’s type questionnaires developed by the researcher. The scale was based on four sub-constructs of providing a better learning environment, effective communication, teaching life skills and creating collaboration for learning. Items were developed for measuring teacher classroom performance from literature review and discussion with the teachers. During the past few years, several studies around the world used questionnaires to assess the classroom learning environment (Anderson & Walberg, 2003., Malik & Rizvi, 2018). Initially, 78 items were developed. These items were given to experts for validation with three points Likert Scale as aligned, partially aligned, and not aligned. Some items were deleted and others were reframed in light of their opinion. At this stage, 65 items were left. The content validity index is .83 which is excellent (Rodrigues, Adachi, Beattie & McDermid, 2017). The scale was administered to 200 teachers on five points Likert Scale with 1 for never, 2 =rarely, 3=sometimes, 4=often, and 5= always. Reliability statistics were run on the respondent. After applying reliability if the item was deleted, the final scale has 50 items with a Cronbach alpha value of .92. As the study is multimethod, means data collection was more than one method. For this purpose, an observation schedule was prepared. The observations were collected for 40 minutes. According to Merriam (1998) there is no ideal time for observation and Freankel & Wallen (2003) advice for multiple observations of limited duration with 30 seconds interval between observations. With the assistance of the observation schedule, observers filled five points on the Likert Scale immediately after completing the observation. In the five-point Likert's Scale, an item was recorded as never noticed if it had never been observed before. If an object was noticed once, it was rarely ticked, twice as frequently, thrice as often, and four or more times was always ticked (Wragg, 2003). The Likert's Scale was then coded according to the quantitative data format. The researcher along with another observer conducted the observation. Before conducting actual observation, the observer got online training for improving observation skills and practiced the data entry process in classrooms, which were later excluded from the sample. The observers were specially made aware to control their bias during observation. Bias awareness in this context includes searching for what has been in the observation instrument rather than looking at the teaching process with his lens. The activity was performed multiple times until the primary goal of observer training, which was to ensure that data was entered repeatedly in the same category, was met. (Joe, Tocci, Holtzman, William,2013). For reliability, the instrument was pilot studied in 08 classes equally distributed by gender. Inter-rater reliability was .92. Methodology The study is multi-method study. Creswell & Plano (2018) defines multimethod research as a type of research that has multiple forms of qualitative data (interview and observation) or multiple forms of

52 quantitative data (survey and experimental). Creswell & Plano (2018) further differentiate it from mixedmethod research which uses data from two different paradigms i.e., qualitative and quantitative data. According to Fetter & Azorin (2017), multiple methods refer to all the various combinations of methods that include in a substantive more than one data collection procedure. The current research combines two types of quantitative data. One set of data was collected through self-report measures and the other was quantitative observational data. Population of the Study The population of the study includes all schools working under the Federal Directorate of Education, Islamabad. There were 392 schools (both male and female) with 6442 teachers as per the Annual Educational Census 2013-14. The population of schools in all the five sectors of Islamabad along with the population of teachers is shown in table 1. Table 1 The population of Schools and Teachers Education Sectors Total Schools Number of Teachers Female Male Female Male Bara Kau 38 41 548 430 City-Urban 95 21 1616 1323 Nilore 41 27 428 395 Sihala 42 32 537 476 Tarnol 23 32 358 331 Total 239 153 3487 2955 Grand Total 392 6442 Source: http://fde.gov.pk/institutions.html Sample As the population is divided into different strata, so, stratified random sampling was adapted. The number of schools included in the sample is 156 (40%) of the total schools. These have been drawn from each stratum according to the population of that strata. Sample from each stratum should be drawn according to the population of the stratum (Kothari, 2009 & Fowler, 2014). For the stratified random sampling of teachers from the above 156 schools as per the sampling selection procedure of schools, the sampling error formula is given by Fink & Kosekoff (1985) and Fowler (2014) was used.

53 Using stratified random sampling, proportionate to the population of each stratum from 156 schools a total of 1500 teachers were drawn. The population was further drawn according to gender, level of education and locale population. This strategy ensures the representation of each stratum according to the population of the strata. Table 2 Description of the Sample Education Sector Sampled Schools Sampled Teachers Gender Female Male Female Male Education Level Junior Models High Schools Junior Models High Schools Junior Models High Schools Junior Models High Schools Bara Kau 8 7 10 5 45 85 58 44 City-Urban 21 17 00 9 162 214 00 300 Nilore 11 5 8 3 40 65 61 29 Sihala 9 8 9 4 40 82 53 58 Tarnol 3 6 7 6 17 67 31 49 Sub-Total 52 43 34 27 304 513 203 480 Total 95 61 817 683 Grand Total 156 1500 Finding Both set of data sets were subjected to statistical analysis to find whether there is any significant difference between the two sets of data. For this purpose, independent sample t-test was applied. Result of the analysis is given in table 3.

54 Table 3 Comparison of Data Collected through Questionnaire and Observation About Teachers’ Classroom Performance. Scale/sub-construct Data Type No. of Items Mean P TCP Self-Reporting Data 50 4.20 .132 Observational Data 50 4.11 LE Self-reporting Data 23 4.25 .766 Observational Data 23 4.22 EC Self-Reporting Data 05 4.26 .875 Observational Data 05 4.30 Life Skills Self-Reporting Data 10 4.10 .784 Observational Data 10 4.07 Collab Self-Reporting Data 12 4.15 .000 Observational Data 12 3.84 Note. LE=Learning Environment, EC=Effective Communication, LS=Life Skills, Collab=Collaboration, Rating based on a five-point metric (1=Never to 5=always) When the mean score of each item of teachers’ classroom performance scale on both self-reporting and observational data was analyzed for finding significant difference using a independent-sample t-test, it was found that the two data sets did not differ significantly with p=.132 at (p<.05). Among the sub-scales, the two data set differ significantly in collaboration with p=.000 at (p<.05). The self-reporting (M=4.15, sd=.19) and observation (M=3.84, sd=.36, t(98)=1.52, p=.000). The magnitude of the difference in the mean score (Mean difference .08, 95%, cl=-.0273 to .206). The Eta Squared calculated is 0.31 mean moderate. 0–0.20 = weak effect, 0.21–0.50 = modest effect, 0.51–1.00 = moderate effect, >1.00 = strong effect as reported by (Cohen, Manion & Morrison, 2018). But the other three sub-scales did not differ significantly with p=.766, .875, and .784 for the learning environment, effective communication, and life skills respectively. It means the among the four sub-scales teachers scored similar on three sub-scales but varied in one. Eta squared values (Cohen’s d) have been calculated using the effect size calculator. For all the effect size, in this case, is 0.2, which means the effect is small. Finding The mean score of self-reported scale and quantitative observational scale of teachers’ classroom performance corresponds to “often” the item response reveals that teachers correctly reported their performance.

55 That there is no significant difference in the mean score of the self-reported and quantitative observational score, demonstrates that teachers reported their behavior correctly. However, on subconstructs create collaboration for learning the difference is significant. Teachers have reported themselves higher on these constructs. Discussion Self-reports continue to be a valid way for assessment in education and psychology (Pekrun, 2020). Selfreport assessment, in contrast to other methods of assessment, enables evaluation of all varieties of psychological processes. Observation, achievement exams, neuroimaging, and other methods can all be used to evaluate behaviour that is readily apparent. Self-report can be used to evaluate all of the affective, cognitive, physiological, and behavioural processes that are a part of self-regulated learning because all of these processes can be represented in the human mind and can be reported accordingly. Physiological measures the arousal of peripheral systems. Second, self-report is the only method that can provide a distinct evaluation of human thought (Pekrun & Bühner, 2014). As such, for Self-report is required in order to provide a complex account of feelings, motivation, and metacognition while learning. Finally, self-report is more affordable than alternative approaches. Selfreporting might be the sole technique useful in To further boost its validity, triangulation of different self-report methods (such as open-format and closed items think-aloud protocols) as well as combination of self-report into multi-channel assessments can be helpful. References Abernethy, M., (2015). Self-reports and Observer Reports as Data Generation Methods: An Assessment of Issues of Both Methods. Universal Journal of Psychology 3(1): 22-27, 2015. DOI: 10.13189/ujp.2015.030104. Cohen, L., Manion, L., & Morrison, K. (2018). Research Methods in Education. (8th Ed). London. Routledge. Creswell, J.W., & Plano, V.C. (2018). Designing and Conducting Mixed Method Research. Sage Publishing. New York. Fetter, M.D., Azorin, J. F.M. (2017). Developing Principles for Establishing New Language of Mixed-Method Research. Journal of Mixed Method Research. Vol.II(I). pp.3-10. Sage Publications. Fink, R. and Kosecoff, J. (1985) How to Conduct Surveys: A Step-by-Step Guide? Sage Publications Inc., London. Fowler, F. J. (2014). The Problem with Survey Research. Contemporary Sociology, 43(5), 660–662. https://doi.org/10.1177/0094306114545742f Fraenkel, J. R. & Wallen, N. E. (2003). How to design and evaluate research in education. (5th ed) New York: McGraw-Hill.

56 Joe, J.N., Tocci, C. M., Holtzman, S.L., William, J. C. (2013). Foundation of Observation; Consideration for Development of Classroom Observation System that Help District Achieve Consistent and Accurate Scores. New Jersey. Princeton. Kothari, C. R. (2009). Research Methodology: Methods & Techniques (Second Revised Edition), New Delhi. New Age International Publishers. Merriam, S. B. (1998). Qualitative research and case study applications in education. San Francisco: Jossey-Bass Miles, J., & Shevlin, M. (2001). Applying regression and correlation: A guide for students and researchers. Sage. Mount, M.K., Barrick, M.R., Strauss, P.J. (1994). Validity of Observer Ratings of the Big Five Personality Factors. Journal of Applied Psychology, Vol 79(2), Apr 1994, 272-280. Paulhus, D.L., Vazire, S. (2007). Ch.13 Self-report Method. Handbook of Research Methods in Personality Psychology (pp.224-239). Pekrun, Reinhard. (2020). Commentary: Self-Report is Indispensable to Assess Students’ Learning; Frontline Learning Research Vol. 8 No. 3. Pp. 185 – 193. Pekrun & L. Linnenbrink-Garcia (Eds.). (2014). International handbook of emotions in education (pp. 561-579). Taylor & Francis. Wragg. E.C. (2003). An Introduction to Classroom Observation. (2nd Ed). London. Routledge

57 PER 05-01-22 A Comparison of Teaching Proficiency of Science Teachers Having B.S. Education. Degree and B.Sc. B.Ed. Degree DR. MUHAMMAD BASHARAT Teacher, Federal Directorate of Education, Islamabad [email protected] ABSTRACT No doubt, Teachers’ teaching proficiency plays an important role in bringing about change in the circumference of educational institutions, which will make learning more effective and of higher quality for all. The main objective of the present study was a comparison of teaching proficiency of science teachers having B.S.Ed. degree and B.Sc. B.Ed. degree. The study was descriptive in nature and based on survey through questionnaire. Population was grouped and sample was multigrade random. All Head Teachers, Science teachers and students at secondary school level in Islamabad Model Schools were population. The data was analyzed and interpreted by using simple statistical techniques of percentage, mean, standard deviation, t-test and chisquare. The results of the study showed that B.Sc. B.Ed. science teachers have better teaching proficiency when compared with B.S.Ed. science teachers. The curriculum of B.S.Ed. program needs revision. Revised curriculum may include content to improve the subject mastery and knowledge of the subject. Key Words: Teaching, Proficiency, Science, Teacher, B.Sc. B.Ed., B.S. Education.

58 I. INTRODUCTION Importance of education as a catalyzing agent that provides mental, physical, ideological, and moral training to individuals cannot be denied by anyone. It enables them to be aware of their purpose. It helps in spiritual development as well as helps in fulfillment of materialistic human needs. According to Mishra (2005), it is a teacher who makes a child socially acceptable, who provokes and promotes the capabilities of a child to their fullest and best. In order to all this, teacher has to act like a facilitator, like a counselor, and like a philosopher. According to Din (2008, p.24), the quality of any educational system depends on the competency of teachers. Teachers are irreplaceable with any other instructional material. Whole system of a school depends on teachers. They can make the system successful. A teacher is more important than what is usually considered. Their duties are multidimensional. II. Literature Review A. Teacher A teacher is a person who teaches children and adults. Responsibilities of a teacher are multidimensional, formal, and ongoing. Different cultures demand a different role from a teacher. In an illiterate scenario teacher’s primary role may be of an educator, professional trainer, or facilitator in life skills and experiences. A teacher is known as a tutor who is actually a facilitator, who facilitates an individual in seeking education (Suleman, 2000). B. Teaching In a narrow perspective imparting instructions in classroom setting is known as teaching. In wider perspective it is a product of many activities. It includes communication between the

59 teacher and student, preparation of lesson planning, preparation and collection of instructional material, teaching aids, and selection of assessment tools etc. Anees (2001), states that there is a great confusion regarding definition of teaching. Teaching is very difficult to define even in classroom settings. Teaching is a collection of many different acts that different teachers perform in different situations. It varies from environment to environment and from person to person. Teaching is the art of facilitating someone to learn. It includes instructions, activities and situations which are designed to help learners in learning. It is actually an interaction between a teacher and learner where teacher through directed activities tries to bring a desired change in learner’s behavior. C. Teaching Proficiency Research offers many definitions of a proficient teacher. Clark (1993), states that a simple definition to describe an effective teacher can be he/she is the one who can enhance student knowledge but he is far more than that. Vogt (1984), states that the efficient teacher is the one who teaches students of mixed abilities and deals them individually and attains his educational objectives successfully. Clark (1993) reports that Collins (1990) worked with a teacher assessment project, during that he developed five criteria for an effective teacher. These are: • Possess subject mastery • Holds responsibility of managing students • Is committed to learning and his/her students • Thinks systematically about his/her practice • Is a member of learning community

60 According to Sheekly & Keeten (1999), a teacher is proficient if he/she has the ability to apply knowledge in a skillful manner within a specific domain. To measure proficiency one should select a set of rules and competencies before testing it. Set of competencies varies with respect to different domains. Interstate New Teacher Assessment and Support Consortium (INTASC) has developed a set of ten standards that is applicable to all disciplines, all grade levels and for almost all teachers. These are: • knowledge of the content; • knowledge of relationship between development and learning; • selection of teaching method that satisfies individual needs; • multiple instructional methods; • skillful use of motivational techniques; • skillful use of communication skills; • effective instructional planning; • use of best assessment methods for student learning; • sense of responsibility and determination; and • Partnerships (Campbell, 2001). Proficient teachers are well aware of unique backgrounds of students to understand their individual differences, their cultural and social characteristics, and their individual needs. They develop learning environment which is productive, safe and positive for all the students. Teacher’s proficiency is well depicted by his/her teaching programmes that fulfill requirements of assessment, reporting and curriculum implementation. Teaching proficiency demands that

61 teachers are engage in reflective practices of critical thinking about their professional development, and they become active learners to keep their knowledge update (Teacher Educator, New South Wales Validation Survey 2, 8 October to 5 November 2010). Effective teachers perform different roles in different situations. They keep changing their roles in different situations. For example, a teacher’s performance is most effective to capture the interest of students in one situation. In any other situation he/she performs to motivate students and in the other students he takes the role of a guide or counselor to a student. There are many factors which effect the quality of education and among these most important is the teacher. They have direct impact on the knowledge, attitudes and development of students. Many researches indicate a positive correlation between teacher competency and student achievement. Darling &Hammond (2000), state that the more prepared teachers are to comprehend content; design activities prepare methods of evaluation, respond to student perspective, the more successful they are as teachers and more successful their students become. Arshad & Akram (2013) conducted a research compared trained teachers regarding proficiency. They declared that the trained ones are much better in their presentation. In a study Sadruddin (2013) found that when one year bachelor of education program of Pakistan when compared with other countries, there exists a gap in the curriculum of both. Ali and Parveen (2013) stated that student learning activities become much purified when teachers are professionally trained. Most of developed and developing countries take teaching practice as a very serious matter. In order to produce well trained teachers, proper policies and their proper implementation regarding teacher education is needed. This is the only way out to improve quality of education.

62 As teachers are the pillars of education system, no education system can be successful without competent teachers. According to Sapieha (2007) teachers actually perform the task of personality development so their training, their competency and their commitment to their task, their quality of teaching and their teaching learning environment all are very important for the well being of students. D. Pre-Service Training and Teaching Proficiency According to Sapieha (2007), teachers’ personal qualification, their professional training, their skill to teach, their personal interest in teaching, the atmosphere in which they teach, their attitude towards students, their quality of teaching, their interest in the well being of students all are the factors which directly influence teaching of a teacher. Borman, Kimball (2005) and Ball (1990) have stated very clearly that in teaching and learning process, pedagogy is most important. Ballou & Podgursky (2000) has further elaborated the fact that pedagogical aspects of teaching have great impact on student achievement as well. Gitomer & Latham (1999) through their study has clearly described that teacher preparation and their performance in the class have a very positive relationship. Gyton & Farokhi (1987) have a different view on this issue. Their study shows that the ways by which teachers are prepared is of greater importance. Wenligsky, 2000; and Clotfelter, Ladd &Vigdor, 2006, states that prospective teachers join training programs with different previous learning. They join with different qualifications, different experiences and different beliefs about teaching and learning. When they enter real life situations of classrooms their previous learning effect their practices and their work. Shami (2005) in his study states that teachers’ subject knowledge is very strongly correlated to student achievement. If teachers are better qualified then students show better

63 achievement. Shami (2005) further elaborates that teachers formal education and subject mastery have more impact on student is performance when compared with their pre-service training. III. STATEMENT OF THE PROBLEM A comparison of teaching proficiency of science teachers having B.S. Education degree and B.Sc. B.Ed. degree. IV. OBJECTIVES OF THE STUDY The following were objectives of the study: i. To examine the teaching proficiency of B.S. Education Science teachers; ii. To assess the teaching proficiency of B.Sc. B.Ed. Science teachers; iii. To compare B.S. Education and B.Sc. B.Ed. Science teachers with regarding to teaching proficiency. V. Hypothesis The following was the hypothesis of the study; H0: There is no significance difference in teaching proficiency of B.S. Education secondary school teachers and B.Sc. B.Ed. Science teachers. VI.Delimitations of the study Due to limited time and resources, the research was delimited as follows: • Public sector educational institutions in Islamabad were studied. • Questionnaire was used as a tool to collect the data. Data was collected only from Head Teachers, Teachers, and Students at secondary schools level.

64 VII. SIGNIFICANCE OF THE STUDY There are many donor agencies which support Pakistan for improving the quality of teachers’ education in Pakistan in shape of grants. The results of study may be significant for donor agencies. The results will be significant for these donor agencies to know the exact position of the teachers’ proficiency and to make future strategy for Pakistan. This research work will also be very important for central government and provincial governments. It will provide guide lines to take correct decision regarding teacher education in Pakistan. The results will be beneficial for the policy makers and planners to formulate plans and policies in the light of findings of the study. It will open new dimensions of research for future researchers. VIII. RESEARCH METHODOLOGY The procedure of the study was as under: A. POPULATION The population of the study was comprised as following: • Public sector secondary schools in Islamabad (Pakistan); • Heads of above mentioned secondary schools; • B.Sc. B.Ed. Science teachers of above mentioned public sector secondary schools; • B.S. Education Science teachers of above mentioned public sector secondary schools; and • Students of above mentioned schools enrolled at secondary level.

65 B. SAMPLE Multigrade sampling was used. In order to ensure adequate representation of the population, the sampling of the study was comprised as following: • 100 Islamabad Model Secondary Schools; • 100 heads of Islamabad Model Secondary schools; • 100 B.S. Education Science teachers; • 100 B.Sc. B.Ed. Science Teachers (equal representation to compare with B.S.Ed.) through convenient sampling technique; and • 600 students from Islamabad model school were selected through random sampling technique. C. TOOLS OF RESEARCH The research instrument for collection of data was questionnaires. The study was survey type therefore a self-developed structured questionnaire was used as research instrument for data collection. It was designed on five point likert scales i.e. A (Always), F (Frequently), O (Occasionally), S (Seldom) and N (Never). In order to collect information related to the objectives of the study, three separate questionnaires were developed for each category i.e. a. Questionnaire for Head Teachers b. Questionnaire for Science teachers c. Questionnaire for secondary schools Students All the questionnaires had fifteen close ended statements related to teaching proficiency. Five point rating scale from always to never was used to rate the statements.

66 D. VALIDATIONS OF INSTRUMENTS In order to ensure the trustworthiness of research issue of validity and reliability has to be addressed. Validity refers to the degree to which a research study measures what the research tends to measure. Validity of the questionnaire was got checked by three experts who had doctorate degrees in relevant field. Reliability is the consistency that a data collection procedure demonstrates. According to Best and Khan (1998), Gay (2005), and Masroor (2003), validity refers to the quality of the collection procedure of the data, because it makes a researcher capable of measuring what he/she tends to measure. Cronbach’s alpha reliability test was used to calculate the reliability of questionnaire. • Pilot Testing • Improvement and finalization of instrument E. PILOT TESTING Validation and authentication of the research instrument is imperative to achieve exact and precise results. For this purpose, pilot testing was conducted in 10 percent of the whole population secondary schools to eliminate the weaknesses, misconceptions and ambiguities of the questionnaire. So after pilot testing, questionnaires were revised and then its final version was developed in the light of suggestions given by the experts in the field of education. F. IMPROVEMENT AND FINALIZATION OF INSTRUMENTS The questionnaires about the teaching proficiency of Science teachers having B.S. Education & B.Sc. B.Ed. degrees was developed in English and was revised in the light of feedback received

67 after pilot testing. Each questionnaire was improved in the light of their comments. The researcher approached each respondent personally. The researcher kept on taking note about any difficulty faced by respondents. The questionnaires were refined on the basis of responses of the respondents. Those statements, for which respondents asked for explanation or they took more time to understand, were revised. G. PROCEDURE OF DATA COLLECTION For the collection of data the researcher personally visited the sample schools to administer and collect the questionnaires, 99% questionnaires were collected during the visit whereas 1% was received by mail, with 100% responses rate. After reaching the schools the Head Teachers were contacted a n d effort was made to establish a good rapport with the mand the questionnaires were distributed to them within the school hour, difficult terms were first explained and then the participants were told to give correct response without any hesitation and free of bias. They were requested to give their free opinions which would be kept confidential. Confidentiality was strictly maintained. At the same time the science teachers were requested to give their opinion freely and completely; they were assure that their opinions would be completely c o n f i d e n t i a l . H. DATA ANALYSIS AND INTERPRETATION Teaching proficiency of B.S.Ed. and B.Sc. B.Ed. Science teachers were assessed with the help of following 12 tables. The data collected by questionnaire meant for the head teachers and teachers was treated in appropriate ways. It was tabulated, analyzed and interpreted in the light of objectives of the study. The questionnaires were developed on five points rating scale (Always, frequently, occasionally, seldom and never). For scoring process the responses always, frequently,

68 occasionally, seldom and never were assigned 5, 4, 3, 2 and 1 marks respectively for the closed ended statements. Significance of difference between the mean score values of the responses of students about B.S. Education Science teachers and B.Sc. B.Ed. Science teachers were tested by t-test. p-value for significance differences at 0.05 level of confidence. Table 1: Frequencies and percentage of student participants along with demographics. Demographics f % Students of the Teacher B.S. Education 300 50 B.Sc. B.Ed. 300 50 Table 1 represents the distribution of the sample students of secondary school teachers. Table indicates that 50% respondents were students of B.S. Education teachers and 50% respondents were students of B.Sc. B.Ed. teachers. Descriptive, alpha-coefficient and ranges for students’ instrument (questionnaire) regarding Teaching Proficiency in order to present the study results in summarized from means and standard deviations were computed for each variable of the study. Table 2: Psychometrics Properties of students’ instrument (questionnaire) regarding teaching proficiency (N = 600). Scales No of items α M(SD) Ranges Potential Actual Teaching Proficiency 15 .85 60.05(10.48) 15-75 27-75 Table 2 shows the psychometric properties of students’ instrument (questionnaire) used in the study. Teaching Proficiency has acceptable Cronbach Alpha reliability and descriptive statistics.

69 Table 3: Means, Standard Deviations and t-values on teaching proficiency between students of B.S. Education and B.Sc. B.Ed. Teachers (N=600). Variable B.S. Education (n = 100) B.Sc. B.Ed. (n = 100) t(598) p 95 %CI Cohen’s D M SD M SD LL UL Teaching Proficiency 54.72 10.04 65.38 7.88 -14.54 .000 -12.10 -9.22 -1.18 Table 3 shows the results of t-test for comparing students of B.S. Education and B.Sc. B.Ed. teachers on teaching proficiency scale. The table shows that students were of the view that B.Sc. B.Ed. teachers have higher teaching proficiency as compared to B.S. Education teachers. The mean difference 10.66 is highly statistically significant between students of B.S. Education and B.Sc. B.Ed. teachers on the score of teaching proficiency as p <.05. Table 4: Frequencies and percentage of teacher participants along with demographics. Demographics f % Teachers B.S. Education 100 50 B.Sc. B.Ed. 100 50 Table 4 represents the distribution of the students of secondary school teachers. Table indicates that 50% respondents were B.S.Ed. teachers and 50% respondents were B.Sc. B.Ed. teachers. Descriptive, alpha-coefficient and ranges for teachers’ instrument (questionnaire) regarding Teaching Proficiency in order to present the study results in summarized from means and standard deviations were computed for each variable of the study. Table 5: Psychometrics Properties of teachers’ instrument (questionnaire) regarding teaching proficiency (N = 200).

70 Scales No of items α M(SD) Ranges Potential Actual Teaching Proficiency 15 .81 58.90 (8.80) 15-75 27-75 Table 5 shows the psychometric properties of teachers’ instrument (questionnaire) used in the study. Teaching Proficiency has acceptable Cronbach Alpha reliability and descriptive statistics. Table 6: Means, Standard Deviations and t-values on teaching proficiency between B.S. Education and B.Sc. B. Ed. Teachers (N=200). Variable B.S.Ed. (n = 25) B.Sc. B.Ed. (n = 25) t(198) p 95 %CI Cohen’s M SD M SD LL UL D Teaching Proficiency 58.41 9.61 59.39 7.89 -1.47 .142 -2.28 0.33 -0.11 Table 6 shows the results of t-test for comparing B.S. Education and B.Sc. B.Ed. teachers of secondary schools on teaching proficiency scale. The table shows that there is no significant difference between B.S. Education and B.Sc. B.Ed. teachers regarding teaching proficiency. The mean difference 0.98 is statistically non significant between B.S. Education and B.Sc. B.Ed. teachers on the score of teaching proficiency as p >.05. Table 7: Frequencies and percentage of Head Teacher participants along with demographics. Demographics f % Head Teachers of Teachers B.S. Education 50 50 B.Sc. B.Ed. 50 50

71 Table 7 represents the distribution of the head teachers of secondary schools. Table indicates that 50% were head teachers of B.S. Education teachers and 50% were head teachers of B.Sc. B.Ed. teachers. Descriptive, alpha-coefficient and ranges for head teachers’ instrument (questionnaire) regarding Teaching Proficiency in order to present the study results in summarized from means and standard deviations were computed for each variable of the study. Table 8: Psychometrics Properties of head teachers’ instrument (questionnaire) regarding teaching proficiency (N = 100). Scales No of items α M(SD) Ranges Potential Actual Teaching Proficiency 15 .87 56.58(9.58) 15-75 34-75 Table 8 shows the psychometric properties of head teachers’ instrument (questionnaire) used in the study. Teaching Proficiency has acceptable Cronbach Alpha reliability and descriptive statistics. Table 9: Means, Standard Deviations and t-values on teaching proficiency between head teachers of B.S.Ed. and B.Sc. B.Ed. teachers (N=100). Variable B.S.Ed. (n = 25) B.Sc. B.Ed. (n = 25) t(98) p 95 %CI Cohen’s M SD M SD LL UL D Teaching Proficiency 51.70 8.14 61.37 8.45 -5.86 .000 -12.95 -6.39 -1.17 Table 9 shows the results of t-test for comparing head teachers of B.S. Education and B.Sc. B.Ed. teachers of secondary schools on teaching proficiency scale. The table shows that the head teachers were of the view that B.Sc. B.Ed. teachers have higher teaching proficiency as compared

72 to B.S. Education teachers. The mean difference 9.67 is highly statistically significant between head teachers of B.S. Education and B.Sc. B.Ed. teachers score on teaching proficiency as p<.05. IX. FINDINGS AND RESULTS B.Sc. B.Ed. teachers have better teaching proficiency when compared with B.S.Education teachers, they better express subject mastery; they teach class with better preparation; they check their students’ homework properly and regularly; they better assess their students’ academic achievements by arranging weekly/monthly test; they frequently use laboratory apparatus and equipments to clear students’ concepts; they allow students to ask relevant question during the lecture; they better participate in new roles other than teaching (e.g., organization, management, monitoring); they always avail the opportunities of in service training related to the subject; they complete assigned tasks on time. IX.DISCUSSION H0: There is no significance difference in teaching proficiency of B.S. Education secondary school teachers and B.Sc. B.Ed. secondary school teachers. Answer of this null hypothesis is found with the help of three tables. The results of t-test for comparing students of B.S. Education and B.Sc. B.Ed. teachers on teaching proficiency scale. The table 3 shows that students were of the view that B.Sc. B.Ed. teachers have higher teaching proficiency as compared to B.S. Education teachers. The mean difference 10.66 is highly statistically significant between students of B.S. Education and B.Sc. B.Ed. teachers on the score of teaching proficiency as p <.05. The results of t-test for comparing B.S. Education and B.Sc. B.Ed. teachers of secondary schools on teaching proficiency scale. The table 6 shows that teachers were of the view that there is no significant difference between B.S. Education and B.Sc. B.Ed. teachers regarding teaching

73 proficiency. The mean difference 0.98 is statistically non significant between B.S. Education and B.Sc. B.Ed. teachers on the score of teaching proficiency as p >.05. The results of t-test for comparing head teachers of B.S. Education and B.Sc. B.Ed. teachers of secondary schools on teaching proficiency scale. The table 9 shows that the head teachers were of the view that B.Sc. B.Ed. teachers have higher teaching proficiency as compared to B.S. Education teachers. The mean difference 9.67 is highly statistically significant between head teachers of B.S. Edcation and B.Sc. B.Ed. teachers score on teaching proficiency as p<.05. It is clear from the above results that there is a significance difference in teaching proficiency of B.S. Education secondary school teachers and B.Sc. B.Ed. secondary school teachers. B.Sc. B.Ed. teachers have higher teaching proficiency as compared to B.S. Education teachers, so H01 is rejected. X. CONCLUSION i. B.Sc. B.Ed. teachers have better teaching proficiency when compared with B.S. Education teachers. ii. B.Sc. B.Ed. teachers better express subject mastery. iii. B.Sc. B.Ed. teachers teach class with better preparation. iv. B.Sc. B.Ed. teachers always avail the opportunities of in service training related to the subject. XI.RECOMMENDATIONS i. B.S. Education teachers are found less proficient therefore their teaching program need improvement. It is recommended that the curriculum of their teaching program need revision. Revised curriculum may include content to improve the subject

74 mastery and knowledge of the subject. Higher Education Commission must take initiative in this regard. ii. It is recommended that in-service training should be arranged for the existing B.S. Education teachers in order to equip them with techniques of classroom management and the latest teaching methodologies so that the existing gap may be filled. Training wing of Federal Directorate of Education may work under the guidance of ministry of Capital Administration Development Division to develop and practice such inservice training programs. Short term workshops can be very fruitful. iii. Lack of incentives for teachers has created a professional inertia among them. To improve the teaching proficiency of teachers, it is recommended that performance based rewards in the forms of trophies, certificates, shields, cash prizes and promotion must be introduced. Federal Directorate of Education may formulate some criteria for such incentives. Different programs may be arranged for such ceremonies. Non-Government organizations may be encouraged to work in collaboration with Federal Directorate of Education to bear expenses of such programs. iv. A transparent and fair policy for teacher recruitment is the need of time. Government should ensure that merit is observed for recruitment of teachers to improve the quality of teacher. v. Content and methodology both must be focused during teacher training programs to improve the quality of teachers.

75 REFERENCES Ali, M., & Parveen, R. (2013). Teacher training: transition. Dawn. Retrieved from http://ecommons.aku.edu/pakistan_ied_pdck/124 Anees, M (2001). Future trends and dimensions of distance education in Pakistan. (Unpublished) M.Phil. Thesis. Allama Iqbal Open Uiniversity Islamabad. Arshad, M., & Akram, M. (2013). Comparison between the performance of trained and Untrained teachers in Lahore. Global Journal of Human Social Science Linguistics & Education,13(3),86-96. Ball, D. L. (1990a). Prospective elementary and secondary teachers’ understanding of division. Journal of Research in Mathematics Education, 21, 132-144. Ballou, D., & Podgursky, M. (2000). Reforming teacher preparation and licensing: What is The Evidence? Teachers College Record,102, 28-56. Borman, G.D, & Kimball, S.M. (2005). Teacher quality and educational quality: do teachers with higher standards based evaluation rating close students achievements gap? The elementary school journal 106 (1), 23-37 Campbell (2001). How to develop a professional portfolio a manual for teachers. Boston: Allyn and Bacon. Clark, D. (1993, June). Teacher evaluation: Are view of the literature with implications for educators. Unpublished Seminar Paper, California State University at Long Beach. Clotfelter, C.T., Helen, F.L., & Jacob, L. V.(2007a).How and WhyDo Teacher Credentials Matter for Student Achievement? WorkingPaper#2.Washington, DC:CALDER. Collins, A. (1990, March). Transforming theassessmentof teachers: Noteson a theoryof assessment for the21st century. Paper presented at the annual meeting of the National Catholic Education Association, Boston, MA. Darling&Hammond, D. (2000). How Teacher Education Matters? Journal of Teacher Education, 51 (3), pp.145-155 Din, N.M. (2008). Unpublished “A Study of Motivation Techniques Used By Head Of Institutions of Higher Education and Their Impact On The Performance of Teachers” Rawalpindi: University of Arid Agriculture. Gitomer, D. H.,& Latham, A. S. (1999). Theacademic quality ofprospectiveteachers: The impactofadmissions and licensuretesting. Princeton,NJ: EducationalTestingService.

76 Guyton, E., & Farokhi, E.(1987). Relationships among academic performance, basic skills, subject matter knowledge, andteachingskillsofteacher education graduates. Journal ofTeacherEducation,38, 37-42. Mishra R.S (2005) Problems of School Teacher, Common Wealth Publisher Sadruddin, M.M.(2013). Are we preparing global competent teachers? evaluation of The incorporation of global education perspectives in teacher education curriculum in Pakistan. International Journal on New Trends in Education and Their Implications, 4(1),188-202. Sapieha, Shelley. (2007). Essay on Adult Education for Use. RM Advisory University of Calgaryhttp://www.academicsenate.cc.ca.us/Publications/Papers/good_practice_prerequi s.html Retrieved on 20-01-2009 Shami,A.P(2005),EducationinPakistan:PoliciesandPolicyFormulation.Ministryof Education,Islamabad,Pakistan:National BookFoundation. Sheckley, B. G., & Keeton, M. T. (1999).Ecologies that support and enhance adult learning. College Park: University of Maryland College. Shulman, L.S. (2000). Teacher development: Rolesofdomain expertiseand pedagogical knowledge. Journal of Applied Developmental Psychology.21(1).129-135. Teacher Educator, New South Wales Validation Survey 2, 8 October to 5 November 2010 Vogt, W. (1984, Winter). Developingateacherevaluation system. Spectrum, 2(1), 41-46. Wenglinsky, H. (2000). Teachingtheteachers: Different settings,different results. Princeton,NJ: Educational TestingService

77 PER 06-01-22 COMPARISON OF STUDENTS’ ENGAGEMENT LEVEL: AN EVIDENCE OF PUBLIC AND PRIVATE SECONDARY SCHOOLS IN ISLAMABAD Dr.Ehsan Mahmood Principal Islamabad Model College For Boys I-10/1, Islamabad Dr. Javid Iqbal Principal Islamabad Model School For Boys Naugazi, Islamabad ABSTRACT This study aimed to determine and compare cognitive and affective engagement of public and private secondary school students. The study was conducted in Bahria Foundation Colleges Rawalpindi and Islamabad Model Schools for boys Islamabad selecting 150 students of secondary level from each category. Data were collected by administering Students Engagement Instrument (SEI) developed by Appleton, Christenson, Kim, & Reschly (2006) directly to students. The data were analyzed by using independent sample t-test statistical technique to compare the mean score of each category of the students. The findings revealed that public school students have greater vision of future goals and aspirations; whereas, private school student found more motivated than public school students. The public school students created better relationship with teaches as compared to private school students. The private school students had better support of their peers and family in learning activities than public school students. Result and implications have been discussed in detail. KEY WORDS: Students’ Cognitive Engagement, Students’ Affective Engagement. INTRODUCTION The student engagement portrays students’ interest, effort, and time they spend in purposeful educational experiences. It is psychologically involvement of students in learning process, and the extent to which they try to learn, understand the material and incorporate it in their all walk of lives. Students engage when they are involved in their academic work, and they pay attention to comprehend the lesson being taught. Student engagement may be referred to a student's willingness to participate and desire to success in the learning process. The student engagement is the participation in educationally effective practices, both inside and outside the classroom, which leads to a range of measurable outcomes (Kuh et.al, 2007). Krause and Coates (2008) further added that it is the level to which students engage themselves in activities that research has shown to be linked with high-quality learning outcomes. Similarly, the worth of students’ effort which participates to educational activities that contributes to desired outcomes. By way of contrast, others have defined engagement as “the process whereby institutions and sector bodies make deliberate attempts to involve and empower students in the process of shaping the learning experience” (HEFCE, 2008). However, the student engagement is a broad concept which includes the academic as well as non academic activities. Coates (2007) further expressed

78 that these activities are based on active and collaborative learning, participation in challenging academic process, and formative communication with academic staff, involvement in enriching educational experiences. Student engagement has primarily and historically focused upon increasing achievement, positive behaviors, and a sense of belonging in students so they might remain in school. Because the focus was high school completion. Research on student engagement targeted students in middle school and high school, where disengagement typically becomes a concern (Willms, Friesen, & Milton, 2009). More recently, student engagement has been built around the hopeful goal of enhancing all students’ abilities to learn how to learn or to become lifelong learners in a knowledge-based society (Gilbert, 2007). Students participate in these activities at school that creates a sense of belonging with their peers, teacher and value schooling outcomes. On the other hand, some students do not believe their school experience and they do not feel accepted by their classmates or teachers. Gradually these students leave the school, because they are disruptive in class, and exercise a negative influence on schoolmates. Thus, the term student engagement comprises of a psychological component related to students’ sense of attachment with school, acceptance of school values, and students’ conception of school success and a behavioral component pertaining to students’ participation in school activities (Johnson et al., 2001). Students who do not believe they have attachment with school, or refuse school values, are referred as alienated or disaffected students. The participation factor of student engagement is characterized by aspects such as students’ school and class attendance, preparation for class, attending lessons, completion of homework, and their involvement in extra-curricular activities. Since the evolution of this concept many researchers have shown their interest to explore this phenomenon. A number of research studies examined the influence of student engagement have on students. Researchers focused those factors that influence student engagement i.e faculty influence on students’ engagement levels and engagement differences among different groups of college and school students. In this study effort has been made to explore the difference between engagement level of public and private secondary school students of institutions situated in Islamabad capital territory. REVIEW OF LITERATURE Student engagement is a field of growing interest by educational researchers and practitioners. It is considered as an indicator of successful classroom learning and also valued as an outcome of school improvement activities. Students are engaged in academic activities when they are attracted to their work, persist in despite challenges and obstacles, and take visible delight in accomplishing their work. Student engagement also refers to a student's willingness, need, desire and compulsion to participate in, and be successful in, the learning process. Different studies of student engagement examined the factors that influence student engagement as well faculty influence on students’ engagement levels and engagement differences among diverse categories of college and school students. Student engagement expresses areas of cognition, behavior and emotion. Cognitive engagement is a psychological state in which students put in maximum effort to understand a topic and in which they carry on studying for a long period. Fredericks et al. (2004) further categories cognitive engagement into two components: psychological and cognitive. The psychological component

79 includes motivational goals and self-regulated learning as it concerned with thoughtfulness, and willingness to put in the effort to understand complex ideas and master complicated skills. The psychological component stresses students’ motivation to learn. The cognitive component also involves application of learning strategies in thinking and studying. It determines the extent to which students’ are willing to take on the learning task at hand and how long they show persistence in such activities (Richardson & Newby, 2006). Kuh, Kinzie, Schuh, and Whitt (2005) concluded that degree of involvement in academic and cocurricular activities causes the changes in students’ behavior during college life. Pascarella and Terenzini (2005) concluded that students’ knowledge acquisition level and cognitive growth have impact on their increased effort with course content. Ek et.al(2007) conducted a study regional southern university and its results portrayed that students who reside in living-learning communities has a positive effects on their academic engagement and success. Anderman and Kaplan’s (2008) pointed out that student personal relationship with peers play significant role in motivating student towards academic learning and engagement. Kuh et al. (2005) characterize a college or university is educationally effective if it focuses on students’ energies toward suitable activities and engages them at a high level in these activities. National Survey of Student Engagement (NSSE) is used by colleges and universities to assess campus climate and student levels of engagement through student self-assessment method. The major purpose of NSSE is to evaluate students’ engagement behaviors such as time spent for studying class or the amount of interaction with faculty, staff and peers. It identifies the status of institutions’ levels of student engagement and describes ways of improving practices that may increase students’ engagement. The NSSE survey also collects information regarding students’ background and differences among groups (NSSE, 2009). NSSE survey results have been used to determine engagement level and its impact on college readiness (Kuh, 2007), student learning (Carini et al., 2006), grades and persistence (Kuh et al., 2007), instructional methods (Ahlfeldt et al., 2005), and faculty influence on student engagement levels (Umbach & Wawrzynski, 2005). NSSE survey results also identified characteristics among student group (Filkins & Doyle, 2002), gender differences (Harper, Carini, Bridges, & Hayek, 2004). METHODOLOGY The study was descriptive in nature and a survey was conducted to collect data from the students on self assessment method. The study was carried out adopting following methodological steps. POPULATION AND SAMPLING The study was carried out during the academic session 2014-15. One hundred and fifty (150) secondary level students from three Islamabad Model secondary schools for boys, and one hundred and fifty students from three Behria colleges (secondary level classes) Islamabad were randomly selected. The target population of this study constituted a sample of 300 secondary level students. INSTRUMENT

80 The study was conducted by using Student Engagement Instrument (SEI) developed by Appleton, Christenson, Kim, & Reschly (2006) to measure students’ cognitive and affective engagement. Student Engagement Instrument consists of 35 items which include 3 constructs of students’ cognitive engagement i.e. ‘control and relevance of school work’, ‘future goal and aspirations’ and “extrinsic motivation” and three factors of students’ affective engagement i.e. ‘teacher student relationship’, ‘peer support for learning’ and ‘family support for learning’. This instrument was developed on 4 point Likert scale having, strongly disagree (1), disagree (2), agree (3) strongly disagree (4) as alternative response. The questionnaires were administered directly to the students and data were collected via students’ self reports. RESEARCH QUESTIONS Following two research questions were postulated and tested by applying independent sample ttest. Q.1: What difference does exist between private and public secondary school students’ “cognitive engagement constructs”? Q.2: What difference does exist between private and public secondary school students’ “affective engagement constructs”? ANALYSIS The inferential statistics techniques ‘independent sample t-test’ was conducted to compare mean scores of each construct of students’ cognitive and affective engagement on students’ gender (Boys/Girls) basis. To assess the effect size of independent samples Eta squared values have been calculated and interpreted under the guide lines proposed by Cohen (1988). Which are: 0.01= small effect, 0.06 = moderate effect, 0.14 = large effect. Table 1 Comparison of Public and Private Secondary School Students’ Cognitive Engagement Constructs Factors of Cognitive Engagement School Type N Mean SD T P Control and Relevance of School Work Public 150 3.33 0.32 -1.39 0.164 Private 150 3.27 0.46 Future Goals and Aspirations Public 150 3.34 0.32 -6.01 *0.000 Private 150 3.10 0.39 Extrinsic Motivation Public 150 2.69 0.58 4.18 *0.000

81 Private 150 2.98 0.61 * p <0.05 Table 1 presents the comparison of public and private secondary school students’ cognitive engagement factors by conducting independent sample t-test and depicts that: 1. There is no significant difference between the mean scores of “Control and Relevance of School Work” of public and private secondary school students, as ρ=0.164 (ρ>0.05), for public school students (M=3.33, SD=0.32) and for private school students (M=3.27, SD= 0.46); t (298) = -1.39. It is obvious that there no considerable difference between public and private school students’ mean scores in “Control and Relevance of School Work”. There is significant difference between the mean scores of “Future Goals and Aspirations” of public and private secondary school students, as ρ=0.00 (ρ<0.05), for public school students (M=3.34, SD=0.32) and for private school students (M=3.10, SD= 0.39); t (298) = -6.01. It is obvious that public school students mean score is greater than private school students’ mean score in “Future Goals and Aspirations”. The magnitude of difference in the means by calculating effect size is small (Eta squared = 0.00). There is significant difference between the mean scores of “Extrinsic Motivation” of public and private secondary school students, as ρ=0.00 (ρ<0.05), for public school students (M=2.69, SD=0.58) and for private school students (M=2.98, SD= 0.61); t (298) = 4.18. It is obvious that private school students’ mean score is greater than public school students’ mean score “Extrinsic Motivation”. The magnitude of difference in the means by calculating effect size is small (Eta squared = 0.002). Table 2 Comparison of Public and Private Secondary School Students’ Affective Engagement Constructs Factors of Cognitive Engagement School Type N Mean SD t P Teacher Student Relationship Public 150 3.38 0.32 -3.18 *0.002 Private 150 3.24 0.42 Peer Support for Learning Public 150 2.99 0.35 3.27 *0.001 Private 150 3.14 0.45 Family Support For Learning Public 150 3.16 0.33 2.68 *0.008 Private 150 3.28 0.43 * p <0.05 Table 1 presents the comparison of public and private secondary school students’ affective

82 engagement factors by conducting independent sample t-test and depicts that: There is significant difference between the mean scores of “Teacher Student Relationship” of public and private secondary school students, as ρ=0.002 (ρ<0.05), for public school students (M=3.38, SD=0.32) and for private school students (M=3.24, SD=0.42); t (298) = -3.18. It is obvious that public school students mean score is greater than private school students’ mean score in “Teachers Student Relationship”. The magnitude of difference in the means by calculating effect size is small (Eta squared = 0.002).There is significant difference between the mean scores of “Peer Support for Learning” of public and private secondary school students, as ρ=0.001 (ρ<0.05), for public school students (M=2.99, SD=0.35) and for private school students (M=3.14, SD= 0.45); t (298) = 3.27. It is obvious that private school students’ mean score is greater than public school students’ mean score “Peer Support for Learning”. The magnitude of difference in the means by calculating effect size is small (Eta squared = 0.002). There is significant difference between the mean scores of “Family Support for Learning” of public and private secondary school students, as ρ=0.008 (ρ<0.05), for public school students (M=3.16, SD=0.33) and for private school students (M=3.28, SD= 0.43); t (298) = 2.68. It is obvious that private school students’ mean score is greater than public school students’ mean score “Family Support for Learning”. The magnitude of difference in the means by calculating effect size is small (Eta squared = 0.002). CONCLUSIONS The findings of the study depicted that in case of control and relevance of school work both types of the students showed same level of interest. The Islamabad Model School students have greater vision of future goals and aspirations than Bahria Foundation School students. In case of extrinsic motivation Bahria Foundation School students found more motivated as compared to Islamabad Model School students. The Islamabad Model School students created better relationship with teaches as compared to Bahria Foundation School students. Whereas, Bahria Foundation School students have greater support of their peers and family in learning activities than Islamabad Model School students. Overall results depicted that Islamabad Model School students had clear future vision and aspiration related to their study. The Islamabad Model School students also emerged as more social in building relationship with teachers which are more supportive in engaging them in academic activities. Whereas, Bahria Foundation School student found more motivated and gained better support of peers and family in enhancing their learning and academic activities. Results depicted that although Islamabad Model Schools public institutions even then the students of these schools have better future vision and academic aspirations as compared to Bahria Foundation School students. Students of Islamabad Model Schools also create better relationship with teachers; whereas the situation is not the same in Bahria Foundation Schools. The students of Bahria Foundation schools found more motivated than students of Islamabad Model Schools. The students of Bahria Foundation schools also have better peer and family support than students of Islamabad Model Schools. It may be due to their sound and prosperous family background. IMPLICATIONS In the light of study results it is suggested that private school students should be motivated to create in them brighter vision of their future and academic aspirations. The private students should be more social in creating their relationship with teachers. Whereas, the public school students should

83 be motivated to enhance their academic engagement. They should be given more support of their peers and family in enhancing learning activities. REFERENCES Ahlfeldt, S., Mehta, S., & Sellnow, T. (2005). Measurement and analysis of student engagement in university classes where varying levels of PBL methods of instructions are in use. Higher Education Research & Development, 24(1), 5-20. Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. (2006). Measuring cognitive and psychological engagement: Validation of the student engagement instrument. Journal of School Psychology, 44(5). Anderman, L.H., & Kaplan, A. (2008). The role of interpersonal relationships in student motivation: Introduction to the special issue. The Journal of Experimental Education, 76(2), 115- 119. Carini, R., Kuh, G., & Klein, S. (2006). Student engagement and student learning: Testing the linkages. Research in Higher Education, 47(1), 1-32. Coates, H. (2007) A Model of Online and General Campus-Based Student Engagement. Assessment and Evaluation in Higher Education. 32 (2), pp. 121–141. Collecting and Using Student Feedback on Quality and Standards of Learning and Teaching in HE: A report to Higher Education Funding Council for England. Bristol: HEFCE. Filkins, J. W., & Doyle, S. K. (2002). First generation and low income students: Using the NSSE data to study effective educational practices and students. Self-reported gains. Paper session presented at the annual forum of the Association for Institutional Research, Toronto, Canada. Fredricks, J., Blumenfeld, P., & Paris, A. (2004). School Engagement: Potential of the concept, and state of the evidence. Review of Educational Research, 74, 59-109. Gilbert, J. (2007). Catching the Knowledge Wave: Redefining knowledge for the post-industrial age. Education Canada, 47(3), 4-8. Canadian Education Association.

84 Harper, S.R., Carini, R.M., Bridges, B.K. and Hayek, J.C. (2004) Gender Differences in Student Engagement among African American Undergraduates at Historically Black Colleges and Universities. Journal of College Student Development. 45 (3), pp. 271–284. Krause, K., & Coates, H. (2008). Students’ engagement in first-year university. Assessment & Evaluation in Higher Education, 33(5), 493-505. Kuh, G. D. (2007). What student engagement data tell us about college readiness. Peer Review, 9(1), 4-8. Kuh, G.D., Kinzie, J., Schuh, J.H. & Whitt, E.J. (2005) Never Let It Rest: Lessons about Student Success from High-Performing Colleges and Universities. Change: The Magazine of Higher Learning. 37 (4), pp. 44–51. Kuh, G.D., Kinzie, J., Buckley, J.A., Bridges, B.K. & Hayek, J.C. (2007). Piecing Together the Student Success Puzzle: Research, Propositions, and Recommendations. ASHE Higher Education Report, Vol 32, No 5. San Francisco: Jossey-Bass. National Survey of Student Engagement (NSSE) (2009a) Assessment for Improvement: Tracking Student Engagement Over Time. Annual Results 2009. Bloomington, IN:NSSE. Umbach, P.D., Palmer, M.M., Kuh, G.D., & Hannah, S.J. (2006). Intercollegiate athletics and effective educational practices: Winning combination or losing effort? Research in Higher Education, 47(6), 709-733. Willms, J. D., Friesen, S. & Milton, P. (2009). What did you do in school today? Transforming classrooms through social, academic and intellectual engagement. (First National Report) Toronto: Canadian Education Association.

85 PER 07-01-22 Exploring the Self-Regulated Learning Skills of Distance Learners Abida Noreen, M Phil Scholar Department of Distance, Non-Formal and Continuous Education Allama Iqbal Open University, Islamabad, Pakistan. Dr Zaheer Ahmad, Assistant Professor Department of Distance, Non-Formal and Continuous Education Allama Iqbal Open University, Islamabad, Pakistan. Abstract This study aimed at exploring self-regulated learning skills related to goal setting, environment structuring, time management, help-seeking, self-evaluation, and metacognition of distance learners of Allama Iqbal Open University, Islamabad related to education programs. 320 (15% of the total) students were selected out of 2122, which were enrolled in the semester of spring 2019 as the sample for the study. A self-regulated learning scale was developed and administrated to collect the data. The results indicated that all the dimensions of Self-Regulated Learning Skills were often observed by the students in their studies. The "Metacognitive Self-regulation" dimension reflected the highest mean of the six dimensions. Introduction Self-regulation signifies the learner's initiative in taking action. It involves goal-setting and focusing one's actions toward achieving desirable results, as well as self-monitoring (metacognition), time management, and physical and social climate management (Zimmerman & Cleary, 2009). The alternative to conventional schools is increasingly becoming distance learning. Students can benefit from the versatility of distance learning which can lead to a route to higher education for students who don't have the resources or funds to attend conventional universities. Students have expanded their chances for better-paid and more fulfilling careers by pursuing their studies (Kirmizi, 2013). The research objective of the study was to explore the self-regulated learning skills of distance learners enrolled in Allama Iqbal Open University, Islamabad.

86 Self-regulation is more important in the case of distance learners since distance learners are expected to steer their own learning experience. Review of Related Literature The influential theory that supports the theoretical basis for the present study was the SRL theory. Theory of Self-Regulated Learning "Self-regulated learning (SRL) is not a mental ability or ability to perform academically; it is a process of self-direction through which learners turn their mental abilities into academic abilities" (Zimmerman, 2001). Self-regulated learners set targets, create plans to meet their goals, follow their learning goals and reflect on progress and focus on the achievement of their approach after they have accomplished their learning goals. Zimmerman (2001) concluded that self-regulated learners are constructive in their attempts to learn and track their actions to increase performance by being aware of their abilities and deficiencies as learners. Self-regulated learners are intrinsically driven to develop their learning processes. SRL research provides many method models that explain the behavior taken by learners to achieve their desired goals (Carpenter, Endres & Hui, 2020; Kirmizi, 2013). The Concept of Self-Regulated Learning Zimmerman (2008a; 2008b) notes that there are three main aspects of this SRL. At first, it will arouse the inherent motivation of the learners. Second, the students would be meta-cognitively involved in the job. Third, to develop their own modes of learning, learners can actively take initiative. The presumption of self-efficacy as it applies to the power of behavioural motivation is stressed by (Sun, 2009; Price, 2015). He implies that the use of goal-finding, self-evaluation, and self-reinforcement generates and retains an incentive for actions. The basis of self-regulated mechanisms of learning are these processes. Pintrich (2003) suggested that it would be possible for self-regulated learners to try to monitor their actions, motivation, and cognition are established, as well as attainable targets. The SRL method, according to Schunk (2004), includes motivation (self-instruction, attribution, motivation for success, and work value) as well as cognitive patterns (metacognition, self-monitoring, and self-evaluation). SRL and associated mechanisms, such as self-reinforcement, have been studied in the social cognitive sciences, self-instruction (Schunk, 2005), goal-setting, self-evaluation, and self-efficacy (Fung, 2015). It has been developed an immersive theoretical model that can be used to describe the individual SRL mechanism. SRL, according to researchers, requires the learner's

87 will and desire. The learner's motivational orientation of reason, context, and goal is referred to as will. The learner's ability refers to his or her ability to use various perceptual, metacognitive, and resource management strategies. SRL involves three sub-processes, according to Sun (2009): selfobservation or self-monitoring, self-judgment, and self-reaction. Self-observation emphasizes selfrecording and the standard to be met as proof of success. The calculation criteria, the attributes and importance of the goal, and attribution will all influence how people relate their real results to the aim. Inspiration, both environmental and personal, is essential for self-reaction (Taipale, 2017). Personal inspiration contributes strongly to personal growth. When students view their self-esteem as supportive of the learning environment, environmental validation occurs (Queiroz, Garcia, Garcia, Zacares, & Camino, 2020). According to the above hypotheses, SRL is an integrated learning mechanism in which individuals attempt to modify their own behaviour, motivation, and perception to best match their own learning. All authority and goal-setting must arise from inside the student rather than being imposed from without. Individuals' spontaneous and self-directed learning is known as SRL. Dimensions of Self-Regulated Learning Goal Orientation A major component of self-regulatory learning was target orientation or goal setting. Objective orientation was described as the general aims or orientation of learners towards a course (Dunnigan, 2018). Research reveals that in completing classes, target orientation is essential. For example, Beatty-Guenter (2001) defined target orientation as an essential characteristic of those students who have completed their courses. He claimed that it is an essential part of academic achievement to set specific targets. A variety of research studies have also found that productive target setting by distance learners leads to success. (Schrum & Hong, 2002). Physical and Social Environment Management The control of physical and social research settings requires successful management of the environment and the support search (Zimmerman & Moylan, 2009). High achievement is recorded in literature to require greater use of expertise in environmental management (Panadero, 2017). As Lynch and Dembo (2004) also point out because distance learning students are not studying in a structured and controlled classroom setting, they must be able to arrange their own physical learning system, whether at home or elsewhere. Time Management

88 A further aspect of SRL is time regulation. Time control covers "scheduling, scheduling, and managing the study time of one" (Chen, 2002). Literature indicates that time planning and management training allow students to use their study time more effectively (Zimmerman & Campillo, 2003). It is stated that it would take two to three times the amount of time in a webbased course to communicate than in a face-to-face self-regulated learner who knows how to manage their time and can order their learning. Very recently, Nonis et al. (2006) found that institutional and time control approaches are good predictors of academic performance. Help-seeking The willingness to seek instructional aid in an "adaptive way" (Lynch & Dembo, 2004) to facilitate learning is another significant distinguishing feature of self-regulated learners. The significance of help-seeking in distance education was stated by many academics who found help-seeking to be a valuable method for higher achievement. Because distance education students are isolated from classmates and instructors, self-regulated distance education students must be encouraged to seek assistance from others. In this instance, they must successfully employ machines and other measures to reduce the socioeconomic disparity. Self-evaluation One of the primary stages in which people judge their own progress in connection to a specific learning activity is self-evaluation. Distance education students must lead their own learning process because they are isolated from their peers and must direct their own learning. To develop their learning efficiently, distance education students must also have excellent self-evaluation skills. Metacognitive Self-regulation Metacognition is a central feature of SRL. Metacognition requires, as is understood, perception, intelligence, and cognition power. Activities including preparation, control, and regulation are comprised of metacognitive self-regulatory learning. Goal setting and task review are reflected in planning. Efficient self-regulated learners should set appropriate targets and then track and respond to their reviews of the efficacy of their learning practices or techniques. (Zimmerman, 2008a). Self-monitoring should also be regarded as an important element in optimizing learning. Furthermore, learners with high metacognitive knowledge will rely more reliably on their job and remove ineffective learning strategies.

89 Design and Methodology The present descriptive study was survey-type and quantitative in nature. Research Population All postgraduate students studying at Allama Iqbal Open University were included in the research population. These students were related to education programs (B.Ed., M.Ed., and M.A. Education) in the semester of spring 2019 from district Jhelum. Sample of the Study The sample size was 15% of the population and was taken out utilizing a stratified random sampling technique Sampling Technique In this research, the researcher used a stratified random sampling technique and select the sample randomly. The stratified random sampling technique is most suitable for this study because the researcher classified of population and had to collect data from a large population. Research Instrument The self-Regulated Learning Scale (SLS) was developed by the researcher keeping in view the previous research and studies on self-regulation and analyzing the research tools. In particular, Zimmerman (2002)'s self-regulated learning skills were the bases of the developed SLS. The focus of the tool was on the following skills: Table 1 Self-regulated Learning Strategies Strategy Description Goal Orientation General interests of learners or orientation for a course Physical and Social Environment Student-initiated attempts to pick or coordinate the physical world to make learning smoother. Time Management Time management encompasses "planning, scheduling, and managing one's study time." (Chen, 2002)

90 Help Seeking Student-initiated attempts to seek assistance from peers, educators, and adults Self –Evaluation Student-initiated measurements of the consistency or progression of their work Metacognitive Self-regulation Memory, awareness and regulation of perception are part of metacognition. Data Collection The researcher personally visited the workshops that were conducted for the students of B.Ed, M.Ed., and MA Education by AIOU in District Jhelum and select students randomly to collect data using mentioned above research instrument. Due to COVID-19 locked down mode of the workshop was changed therefore researcher converted SLS into an online survey form to easily access the students and got data through online mode. https://tinyurl.com/syzsq6Data were collected both face-to-face and online mode.

91 Analysis Students’ Engagement in Different Self-Regulated Learning Skills Table 2 Mean and Standard Deviation of the SLS (N=288) Dimensions Minimum Maximum Mean Std. Deviation Goal Orientation 1.00 5.00 4.01 0.56 Physical and Social Environment 1.80 5.00 4.15 0.67 Time Management 1.50 5.00 3.72 0.62 Help Seeking 1.50 5.00 3.93 0.61 Self-Evaluation 1.00 5.00 4.06 0.55 Meta Cognitive Self-regulation 2.33 5.00 4.23 0.52 Note. Ratings based on five-point metric (1= strongly disagree to 5= strongly agree) SLS= Self-regulated learning scale Table 2 reflects the descriptive statistics including the minimum, maximum, mean and standard deviation for the Self-Regulated Learning Scale (SLS) on the dimensions of SRL Skills. As illustrated in the table, the SRL Skills dimensions' means ranged from a high value of 4.23 associated with Meta Cognitive Self-regulation, to the lowest value of 3.72 associated with Time Management. Item responses strongly agree (SA) through strongly disagree (SDA) on the SelfRegulated Learning Scale (SLS) were coded so that "strongly agree (SA)" received a score of 5, "agree (A)" received a 4, "undecided (UD)" received a 3, "disagree (DA)" received a score of 2 and strongly disagree (SDA) received 1. All areas' means, which range from 3.72 to 4.23, fall into the agree and strongly agree groups. The findings show that all of the SRL Skills measurements were often found by students during their research. The "Meta Cognitive Self-regulation" dimension has the best average of the six. Results 1. The SRL Skills dimensions' means ranged from a high value of 4.23 associated with Metacognitive Self-regulation, to the lowest value of 3.72 associated with Time Management. The means of all areas ranging from 3.72 to 4.23 fall in the categories of agree and strongly agree. The results indicate that all the dimensions of SRL Skills were

92 often observed by the students in their studies. The "Metacognitive Self-regulation" dimension reflected the highest mean of the six dimensions. 2. The results indicated that all the dimensions of SRL Skills were often observed by the students in their studies. The "Metacognitive Self-regulation" dimension reflected the highest mean of the six dimensions. The SRL abilities of distance education students were examined concerning six self-regulation aspects in this study. Students in remote education see themselves as extremely effective in self-evaluation and metacognitive self-regulation, according to the study. Because distance education students are expected to guide their own learning experience, these two elements are particularly essential. Discussion The study results indicated that all the dimensions of SRL Skills were often observed by the students in their studies. The "Meta Cognitive Self-regulation" dimension reflected the highest mean of the six dimensions. The SRL abilities of distance education students were examined concerning six self-regulation aspects in this study. Students in remote education see themselves as extremely effective in self-evaluation and meta-cognitive self-regulation, according to the study. Because distance education students are expected to guide their own learning experience, these two elements are particularly essential. Recommendations Based on the findings and the unique context of distance education in Pakistan, certain implications and recommendations can be made. 1. Integrating self-regulated learning skills into the distance education curriculum ensures that learners are equipped with the necessary tools and knowledge to self-regulate their learning effectively. 2. Furthermore, providing professional development opportunities for teachers and instructors in distance education can enhance their understanding of self-regulated learning and enable them to support students more effectively.

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