IAFOR Journal of Education

Volume 6 – Issue 1 – Spring 2018

Teachers’ Knowledge Indices as Predictors of Secondary School Students’ Academic
Achievement in Kwara State, Nigeria
Felicia Olasehinde-Williams
University of Ilorin, Nigeria
Lasiele Yahaya
University of Ilorin, Nigeria
Henry Owolabi
University of Ilorin, Nigeria

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Abstract
That less than 40% of candidates who took the Senior School Certificate Examinations in
Nigeria between 2009 and 2015 had credits and above in English language and Mathematics
has become a source of worry to all stakeholders. Results of research efforts to provide
plausible explanations to the problem have been inconclusive. Also, not much had been doneto assess the contribution of teachers’ knowledge indices as likely sources. This study therefore
investigated the predictive value of Teachers’ Depth of Subject Content Knowledge and Depth
of Pedagogical Knowledge on Students’ Academic Achievement in English Language andMathematics. Specifically, the study investigated which category of teachers (B.Ed. /B.Sc.Ed.
/B.A.Ed.; PGDE; or B.A. /B.Sc) had the deepest Depth of Subject Content Knowledge; thedeepest Depth of Pedagogical Knowledge; the deepest Depth of Subject Content andProfessional Knowledge; and the predictive ability of Depth of Subject Content andProfessional Knowledge for Students’ Academic Achievement. The sample comprised
seventy-eight English Language and Mathematics teachers from thirty-two randomly selected
secondary schools in Kwara State; and the intact SS II classes taught by the teachers.
Quantitative data were collected through tests, observations and vignettes; and analysed using
descriptive and inferential statistics. Findings showed that teachers with B.Sc. demonstrated
the deepest Depth of Subject Content Knowledge, Depth of Pedagogical Knowledge and Depth
of Subject Content and Professional Knowledge. Also, pedagogical and subject content
knowledge of teachers were found to be significant predictors of Students’ Academic
Achievement. Significant differences were observed between the Depth of Subject Content
Knowledge and Depth of Pedagogical Knowledge of the English Language and Mathematics
teachers in favor of Mathematics teachers. Similarly, students’ performance in English
Language was lower than that of Mathematics, though not statistically significant. Thesefindings raised concerns of profound implications for teacher education curriculum in Nigeria.
Keywords: teacher knowledge, subject content, pedagogical content, academic achievement,teacher attributes, teacher education curriculum74

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Introduction
Secondary education has remained a major gateway to higher education and employment for
those who may not proceed beyond that level. Most citizens attending schools have thus notconsidered themselves to have been sufficiently prepared to function in the Nigerian society
until they have graduated from secondary schools. Successful completion, and particularly
having credit passes in English Language and Mathematics, are necessary for all secondary
school graduates. Policy on education has made these subjects compulsory to be offered andpassed, as well being required to advance to higher levels of education. There is, however,unsatisfactory performance in certificate examinations at this level as the rate of failure has
been considered high by stakeholders.
The high rate of students’ failure in Senior Secondary Certificate Examinations (SSCE) has
become a perennial source of worry to all stakeholders in the education sector in Nigeria. The
same is true of its equivalents, such as the General Certificate Examination (GCE), and the
University Tertiary Matriculation Examination (UTME). In 2015, for instance, more than 60%
of students failed English Language in the SSCE; while only 38.6% candidates obtained credit
in five subjects including English and Mathematics (West African Examination Council,
2015). There is a need to reverse this trend because poor performance in SSCE leads to colossal
wastage of educational investment and reduction in quantity and quality of candidates
accessing tertiary education. It also limits students’ learning effectiveness which, in turn,compromises quality of tertiary education products in terms of cognate ability and service
delivery competence.
Various efforts by education researchers to provide a valid explanation for the trend have notyielded conclusive results. For instance, Tella (2007) investigated the impact of motivation on
secondary school students’ Mathematics achievement in Nigeria. He reported that there was asignificant difference in Mathematics achievement of students on the degree of theirmotivation. McDonald (2001) also found that two thirds of high school students appeared tohave experienced an uncomfortable level of test anxiety which consequently had a negative
effect on their academic performance.
Any solution to the problem of high failure rates in SSC Examinations should also involve
critical assessment of the contributions of teacher quality in the discharge of their
responsibilities as learning facilitators. Although learning can take place without teaching, theroles of the teacher as facilitator of learning are indispensable in the field of education(Figure 1).

Figure 1: Components of the teaching-learning relationship(Source: Olasehinde-Williams, 2012)75

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As shown in Figure 1, teachers have responsibilities to gather information to determine what
subject content to teach, develop curriculum, determine the strategies and methods for teaching,impart knowledge, evaluate teaching and learning and finally provide feedback. Teachers canonly teach “what” they know in the ways they know “how” to teach. Thus, the significance of
having high quality teachers in the teaching-learning relationship cannot be over-emphasised.
Indeed, the pivotal roles of quality teachers in providing quality education are well documented
in the National Policy on Education (Federal Republic of Nigeria, 2013). The Teachers
Registration Council of Nigeria (TRCN) also noted that “no education system can rise above
the quality of its teachers” (TRCN, 2004, p.8).
Agoro and Akinsola (2013) and Ladipo (2013), for instance, suggested that poor teacher quality
is one of the significant factors responsible for the consistently poor performance of secondary
school students in public examinations in the country. Teacher quality is generally believed to
be basically dependent on the nature of the training that teachers receive and there is no doubtthat teachers differ in their depth of knowledge of the “what” to teach and the “how” to teachbasically because of disparities in their own pre-service training. In Nigerian secondary
schools, for example, two categories of teachers (qualified and non-qualified teachers), fromthree different learning paths, are responsible for preparing students for public examinations.
Two of the three learning paths qualify individuals for the teaching profession in Nigeria.
Firstly, during training, individuals may combine core teacher education courses (Pedagogical
Knowledge) with minor teaching subject courses (Subject Content Knowledge) for a period of
three to four years, for the award of the Bachelor in Education Degree. Secondly, individuals
may first obtain an Honors degree (Bachelor of Science or Bachelor of Arts) in one or two
subjects (Subject Content Knowledge) and later undertake a one-year Postgraduate Diploma in
Education (PGDE) Certificate (Pedagogical Knowledge). Although the proportions of teachingsubject and education courses both groups undertake are not the same, it is generally assumed
that both include sufficient proportions to produce competent teachers (Abimbola, 2012).
Consequently, both categories of teachers are accorded professional teacher status and are
qualified for formal admission into the teaching profession upon registration with the TRCN.
Non-qualified teachers, on the other hand, are individuals who also teach in Nigerian secondary
schools with Honors Degrees in Science, Social Sciences and Arts-related courses without
undertaking any education course at all in the university. Since such teachers have exposure to
Subject Content Knowledge only, without Pedagogical Knowledge, they are categorised as
non-professional teachers and are not qualified for formal admission into the teachingprofession.
These categories of teachers, professional and non-professional, have been receiving criticisms
from major stakeholders in the education sector. In respect to the learning paths to teacher
certification, there are concerns that the teaching subject courses offered by B.Ed/B.Sc. Ed.
/B.A. Ed. graduates, and the pedagogical content knowledge in the PGDE format may not be
sufficiently adequate to make for sufficiently competent and effective teachers. For instance,
education students minor in their teaching subjects and devote a substantial part of their training
to pedagogical knowledge and skills. In the same way, PGDE students would have acquired
more of subject content knowledge since they had earlier obtained their degrees and have thus
also obtained less pedagogical knowledge and skills. Similarly, there are concerns that
unprofessionally trained persons recruited as teachers in Nigerian secondary schools are mostly
graduates in various disciplines that may or may not even be related to the subject that they
were recruited to teach.

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It was assumed in this study that such discrepancies in the professional and academic
qualifications of teachers will likely be reflected in the teachers’ depth of subject content andpedagogical knowledge; in the ways they discharge their roles as facilitators of learning(Henze, Driel & Verloop 2008); and consequently in the ways they impact their students’
academic achievement.
High rates of failure will be unexpected when the teachers and their teaching are very positive,
and the results obtained contradict their input. It is unwanted when effort by the teacher is notstrong enough to bring about expected success. Though the study of secondary school students
in Kenya by Waseka, Simatwa and Okwach (2016) showed the expected result that teacherswith the Bachelor of Education qualification significantly influenced their students’performance, it also revealed the unexpected outcome with the discovery that teachers with the
Master of Education or Diploma qualifications did not significantly influence the performanceof their students. There is a contradiction when holding a higher degree like Master of
Education does not contribute significantly to the prediction of students’ performance. It isnecessary to clarify contradictions like this with research and to particularly determine whether
the teachers have deficiency in subject content or pedagogical knowledge.
The holistic learning theory stressed by psychologists such as Piaget and Bloom provide thetheoretical underpinning for this assumption. Piaget (1936) and Bloom (1956) identified threelearning domains to which students must be exposed: Cognitive Learning (acquisition ofknowledge through direct teaching); Affective Learning (acquisition of feelings, values,
motivation and attitudes through the process of observation); and Psychomotor Learning(acquisition of skills through observation and practice). However, effective and holistic
learning must involve all the three: that is stimulate critical thinking, stimulate interest anddevelop skill.
For instance, Hill, Rowan and Ball (2005) explored whether and how teachers’ mathematicalknowledge for teaching contributes to gains in students’ mathematics achievement. Findingsof the study showed that teachers’ mathematical knowledge was significantly related to
students’ achievement gains in both first and third grades; and provided support for policy
initiatives designed to improve students’ mathematics achievement by improving teachers’
mathematical knowledge. Baumert et al. (2010) investigated teachers' mathematicalknowledge, cognitive activation in the classroom, and student progress. Findings of the study
showed that teachers with a higher PCK score created better lessons, which had positive effects
on the students’ content knowledge and test results.
Adediwura and Bada (2007) investigated perception of teachers’ knowledge, attitude andteaching skills as predictors of academic performance in Nigerian secondary schools. They
found that students’ perception of teachers’ knowledge of subject matter, attitude to work andteaching skills were significantly related to students’ academic performance. In an ongoingstudy related to teacher professional knowledge, Olasehinde-Williams, Yahaya, Sanya,
Owolabi & Jimoh are investigating the comparative effectiveness of teaching strategies(Collaborative, Critical thinking and Technology-integrated teaching strategies) in reducing
secondary school students’ failure in Senior School Certificate English Language Examinationin Kwara State, Nigeria. Preliminary findings of the study suggest the superiority of eachstrategy over the traditional teaching strategy.
Studies by Abell (2007) and Baumert et.al. (2010) have focused on the impact a single teacher
variable on students’ academic achievement. Abell (2007), Park and Oliver (2008) Lee and77

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Luft (2008), and Baumert et.al. (2010) have investigated the impact of teacher variables on
students’ academic achievement in one subject only and they focused especially on Science
subjects. Findings of most of the studies are generally inconclusive (Park & Oliver, 2008).
Besides, most of the studies were conducted in other settings and as such their findings are notdirectly applicable to Nigeria because of socio-cultural differences. Thus, the apparent dearthof studies on the extent to which teachers’ subject content knowledge and pedagogicalknowledge relate to students’ academic achievement in Nigeria made this study imperative.
Literature Review
Critical insights for the study were gleaned from extant literature related to teacher professional
knowledge, data gathering techniques and study approach as conceptualized in this study. As
early as 1987, Shulman had distinguished seven categories teachers’ professional knowledge:
content knowledge; curricular knowledge; pedagogical content knowledge; generalpedagogical knowledge; knowledge of learners and their characteristics; knowledge ofeducational contexts; and knowledge of educational ends, purposes and values (1987).
Subsequently, researchers identified specific components for study, which also informed theirchoice of measurement techniques. For instance, Kirschner, Borowski and Fischer (2010)
focused on three levels of teachers’ knowledge areas (i) declarative knowledge, (ii) proceduralknowledge and (iii) conditional knowledge including teachers’ reactions to critical teachingsituations, which they measured through experiments, teaching strategies and vignettes (thatis, describing short situations in a classroom).
Baumert et al. (2010) focused on teachers’ knowledge of science and the teaching/learning
process as components of teacher professional knowledge and gathered data through paper andpencil tests as well as observation of videotaped lessons. Henze, Driel and Verloop (2008)
focused on teachers’ knowledge about instructional strategies concerning a specific topic;
students’ understanding of the topic; ways to assess students’ understanding of the topic; andgoals and objectives for teaching the specific topic in the curriculum. To measure thesecomponents, in the Netherlands, the researchers followed nine teachers for a period of three
years in their natural settings to see if, and how, their initial Pedagogical Content Knowledge(PCK) developed while they were teaching a new subject.
The Research Study
To address some of the gaps in our current understanding of the important factor of student
academic achievement, this preliminary study investigated the relative contributions ofteachers’ training background to their depth of subject content and pedagogical knowledge aswell as the extent to which teachers’ subject content and pedagogical knowledge improvestudents’ learning outcomes in two core subjects, English Language and Mathematics ,which
are compulsory for all secondary school students in Nigeria. The goal of the study was toestablish the impact of teacher professional knowledge on students’ learning outcomes.
Specifically, 4 research questions were addressed and 3 hypotheses tested in the study.
Research Questions
1. What category of teachers (B.Ed. /B.Sc.Ed. /B.A.Ed.; PGDE; or B.A. /B.Sc.) has thedeepest Subject Content Knowledge?
2. What category of teachers (B.Ed. /B.Sc.Ed. /B.A.Ed.; PGDE; or B.A. /B.Sc.) has themost adequate DPK?

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3. What category of teachers (B.Ed. /B.Sc.Ed. /B.A.Ed.; PGDE; or B.A. /B.Sc.) has thestrongest DSCPK?
4. What is the predictive ability of teachers’ DSCPK for students’ success in examination?
Hypotheses
1. There is no significant difference in the depth of pedagogical knowledge between
sampled English Language and Mathematics teachers.
2. There is no significant difference in the subject matter content knowledge between
sampled English Language and Mathematics teachers.
3. There is no significant difference in the performance between sampled senior secondary
school English Language and Mathematics students.
To these researchers’ minds, empirically determining what mix of teacher subject content andpedagogical knowledge best predicts students’ learning outcomes is critical to reversing thecurrent trend of high failure rate of students in public examinations in Nigeria. Such a reversal,
it was hoped, would enhance the quality and quantity of candidates accessing tertiary
education, enhance the quality of tertiary education products in terms of cognate ability andservice delivery competence and, consequently, boost the nation’s developmental status.
In this study, three components of teachers’ professional knowledge and the extent to which
they impact student learning outcomes were investigated:
1. Depth of Subject Content Knowledge (DSCK);
2. Depth of Professional Knowledge (DPK);
3. Depth of Subject Content and Professional Knowledge (DSCPK), patterned after GessNewsome’s (1999) integrative knowledge category;
4. Students’ Academic Achievement (SAA);
5. Differences in DSCK and DPK of teachers and their SAA in English Language andMathematics; and6. Difference in students’ academic achievement in English Language and Mathematics.
Figure 2, developed by the researchers, presents the schematic representation of how thevariables were controlled.

Figure 2: Schematic representation of DSCK, DPK, DSCPK and SAA(Note:
DSCK: Depth of Subject Content Knowledge, whether Deep or Shallow
DPK: Depth of Pedagogical Knowledge, whether Adequate or Inadequate
DSCPK: Depth of Subject Content and Pedagogical Knowledge, whether Strong or Weak
SAA: Student Academic Achievement, whether High or Low)

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Methodology and Methods
The research design adopted for the study was descriptive survey because of its capacity toallow assessment of certain attributes, properties or characteristics in a situation at one or morepoint in time (Hassan, 1995). Originally, the plan was to sample two hundred Senior Secondary
II (SSII) English Language and Mathematics teachers from 10 randomly selected secondary
schools across the three Senatorial Districts of Kwara State (that is, Kwara North, Kwara
Central and Kwara South), but the reality of the situation in the field altered this plan because
most of the schools had only 1 teacher each for SSII English Language and Mathematics.
Consequently, the number of secondary schools was increased to 32, randomly selected acrossthe three Senatorial Districts of the State. This was done to ensure fair representation of every
part of the State. Thus, all the available SSII teachers of English Language and Mathematics ineach of the 32 schools, totaling 78, participated in the study. These purposively sampled
participants provided data on DSCK and DPK for the study. At the learners’ level, classes of
SSII students of each teacher-participant took part in the study so that their test scores could bereadily matched with their teachers’ DSCK, DPK and DSCPK.
Instruments employed for data collection were paper and pencil tests, used to measure teachers’
DSCK and students’ achievement in both subjects, and observation of teaching strategies andvignettes, that is short classroom situations to which teachers responded to measure their DPK,
because of the potential of such multiple data sources to yield valid, rich, comprehensive andreliable data. Face and content validity, as well as test-re-test reliability measures of theobjective tests and vignettes were determined. Observation of class teaching and management
were subjected to inter-rater validity. The internal consistency reliability measures of the
DSCK and DPK objective tests were 0.94 and 0.82 respectively, while 0.62 and 0.63 wereobtained for the English Language and Mathematics objective tests respectively. All the
instruments yielded quantitative data.
Members of the research team and trained research assistants, comprising lecturers and Ph.D.
students of Educational Measurement and Evaluation, were involved in the data collection.
Ethical guidelines for research and data collection were carefully observed. Data gathering
spanned three weeks and occurred in the second school term to enable substantial coverage ofthe syllabus to enhance the validity of students’ academic achievement. Measures of students’
academic achievement were obtained about one week into the schools’ official examination
period so as not to disrupt the school program and to fall within a period when students
naturally prepared for end-of -term examinations. The maximum possible score on the test ofteachers’ DSCK and DPK was 100%, where 60–100% indicated Deep Knowledge and lessthan 50% indicated Shallow Knowledge. Similar rating was adopted for the students’
Academic Achievement Test, with 60–100% indicating high achievement and less than 50%
indicating low achievement.
Results
Seventy-eight SSII teachers of English Language and Mathematics were sampled as
participants in the study from the three Senatorial Districts of Kwara State, Nigeria. However,
only 75 of them participated fully in the study by making their lesson notes available forinspection, subjecting their lessons to observation, completing the paper and pencil test,
responding to the vignettes and having the students taught by them assessed. The 75
participants comprised 33 female and 42 male teachers. Thirty-nine of the participants were
English Language teachers while the other 36 taught Mathematics. Their ages ranged from 21–

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Volume 6 – Issue 1 – Spring 201860 and they had between 1 and 30 years of teaching experience. Answers to the four researchquestions are presented below.
1. What category of teachers (B.Ed. /B.Sc.Ed. /B.A.Ed.; PGDE; or B.A. /B.Sc.) has the deepest
Subject Content Knowledge (DSCK)?
Assessment of the sampled teachers’ DSCK was carried out through observation of the content
of lessons, taught using the Faculty of Education’s, University of Ilorin, teaching practiceassessment format, and also by responses to a cognate test scored in percentage. The meanscore on both measures was calculated and each category of teachers compared with the mean.
A summary of the assessment is presented in Table 1.
Table 1: Mean Scores of teachers’ Depth of Subject Content Knowledge (DSCK)
Qualification

Frequency

Mean Score in Percentage

PGDE
NCE
B.A. Ed.
B.Sc. Ed.
B.A.
Others
B.Sc.
Total

2
4
21
11
16
8
13
75

44.00
44.75
49.43
57.83
59.69
62.19
65.42
Grand Mean = 56.59

As shown in Table 1, the grand mean of DSCK among teachers was 56.59%. The lowest meanscore was observed among teachers with a PGDE (44%); mean score of 49.43% was obtainedby holders of a B.A. Ed and this was lower than the grand mean. Teachers having a B.Sc. Ed.
degree with a mean score of 57.83% were better than their B.A, Ed counterparts (49.43%);
while teachers with a B.Sc. had the deepest mean DSCK of 65.42%.
2. What category of teachers (B.Ed. /B.Sc.Ed. /B.A.Ed.; PGDE; or B.A. /B.Sc.) has the mostadequate Depth of Pedagogical Knowledge (DPK)?
Sampled teachers were exposed to an assessment of DPK through observation of theirinvolvement in classroom processes, responses to vignettes and personal interview. Based on
their responses, each of them was scored in percentage and the mean score for each categoryof teachers was calculated. A summary of the assessment is presented in Table 2.

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Table 2: Mean Scores of tTeachers’ Depth of Pedagogical Knowledge (DPK)
Qualification
B.A.
NCE
OthersB.A. Ed.
PGDE
B.Sc. Ed.
B.Sc.
Total

N
16
4
8
21
2
11
13
75

Mean Score
41.13
44.75
49.63
50.90
53.00
54.73
56.08
Grand Mean = 49.87

Table 2 shows that, despite generally low levels of depth of pedagogical knowledge, of themean scores demonstrated by the sampled teachers, those holding the B.A. degree had thepoorest mean score of 41.13%; while B.A. Ed., PGDE, B.Sc. Ed. and B.Sc. teachers recorded
above average mean scores of 50.90%, 53%, 54.73%, and 56.08% respectively. The teacherswith the most adequate depth of pedagogical knowledge were those holding the Bachelor of
Science degree (56.08%).
3. What category of teachers (B.Ed. /B.Sc.Ed. /B.A.Ed.; PGDE; or B.A. /B.Sc.) has thestrongest Depth of Subject Content and Pedagogical Knowledge (DSCPK)?
Scores on the measures of DSCK and DPK were added and the mean score for each categoryof teachers summarized as presented in Table 3.
Table 3: Mean scores of teachers’ Depth of Subject Content and Pedagogical Knowledge(DSCPK)
Qualification
NCE
PGDE
B.A. Ed
B.A.
OthersB.Sc. Ed.
B.Sc

Frequency
4
2
21
16
8
11
13

Mean score out of 200
89.50
97.00
100.33100.81111.81112.55
121.50Grand Mean KSCPK = 106.45

The mean DSCPK score was found to be 106.45 as shown in Table 3. Holders of a B.Sc.
demonstrated the strongest DSCPK of 121.50 and they were followed by those with a B.Sc.
Ed. with 112.55. On the other hand, NCE holders had the weakest depth of DSCPK (89.50).
4. What is the predictive ability of teachers’ DSCPK for students’ success in examination?
Students taught by the 75 teachers who participated in this study were tested in those same
subjects and their scores regressed on the assessment of their teachers’ subject content andpedagogical knowledge to determine their predictive value. The results of the regression
analysis are summarized in Table 4.

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Table 4: Prediction of students’ performance by teachers’ Depth of Subject Content andPedagogical Knowledge
Model

R

R
SquareAdjusted
R SquareStd. Error of
the Estimate

R Square
Change

1

.327a

.107

.082

14.43578.107

Table 4 shows a coefficient of multiple correlations (R) of 0.327 which indicated that both
pedagogical and subject content knowledge of sampled teachers were significant predictors ofstudents’ success in examinations. Findings of the study further revealed that the two variables
accounted for 10.7% of the total variance of students’ success in examinations as shown by theR2 of 0.107. An analysis of variance was carried out to ascertain the significance of theprediction of students’ success by their teachers’ subject content and pedagogical knowledge(Table 5).
Table 5: ANOVA of prediction of students’ success by teachers’ Depth of Subject Content
and Pedagogical Knowledge
Model1

Regression
Residual
Total

Sum
of
Squares1768.126
14795.820
16563.946

df
2
71
73

Mean
Square884.063
208.392

F

Sig.

4.242

.018

As shown in Table 5, the F ratio of 4.242 and df of 2, 71 was significant at 0.018 indicatingthat the sampled teachers’ depth of subject content and pedagogical knowledge significantly
predicted their students’ performance. Table 6 contains the summary of the test of thecontribution of each predictor in the regression analysis.
Table 6: Strength of teachers’ Depth of Subject Content and Pedagogical Knowledge in theprediction
Model

1

(Constant)
Pedagogical
ScoresKnowledge
Scores

Unstandardized
Coefficients
B
Std.
Error
44.944
6.859
-.186
.114

Standardized
Coefficients
Beta

.219

.082

t

Sig.

-.186

6.552
-1.633

.000
.107

.304

2.669

.009

As shown in Table 6, the unstandardized regression coefficients of pedagogical and subject
content knowledge were -0.186 and 0.219 respectively and their standardized regression
coefficients were -0.186 and 0.304. Though the two variables were joint predictors of students’achievement, pedagogical knowledge did not contribute significantly to the prediction with at-value significant at 0.107.

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Hypothesis 1: There is no significant difference in the depth between pedagogical knowledgeof sampled English Language and Mathematics teachers.
The F-ratio of the Leven’s test of equality of variances revealed a difference between variancesof depth of pedagogical knowledge of English Language and Mathematics teachers (5.668, p< 0.05) as shown in Table 7. It was further observed that difference existed between the meanof the depth of pedagogical knowledge of teachers of English Language and that ofMathematics teachers (t = -2.034, p < 0.05). These results indicate that there was significant
difference between the depth of pedagogical knowledge of English Language and Mathematics
teachers.
Table 7: Results of Independent Samples Test of Depth of Pedagogical and Subject
Knowledge of Teachers of English Language and Mathematics and their Students’ Scores
Leven's Test
for Equality of
Variancest-test for Equality of Means
95% ConfidenceInterval of theEqual variances
ScoresassumedScoresassumed

t

5.668

.020

-1.99873.049-6.7735

3.39077 -13.53130-.01571-2.03464.389.046-6.7735

3.33091 -13.42699-.12002-2.871

73.005-13.1880

4.59359 -22.34304-4.03303-2.82660.087.006-13.1880

4.66657 -22.52229-3.85378-1.85572.068-6.4000

3.45006 -13.27758.47758-1.85470.934.068-6.4000

3.45250 -13.28419.4841915.712.000

Equal variances
not assumed

2tailed Mean Diff

Diff

DifferenceSig.

not assumed

df

Std. Error

F

Equal variances
Equal variances

Lower

Upper

Equal variances
ScoresStudents’

Knowledge

PedagogicalSigassumedEqual variances
not assumed

0.411

.524

The summary in Table 8 shows that the teachers of Mathematics demonstrated a deeper levelof pedagogical knowledge compared to the teachers of English Language.

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Table 8: Group statistics of teachers’ Depth of Pedagogical and Subject Content Knowledge
and their students’ scores
Variables
Pedagogical
ScoresKnowledge
ScoresStudents’
ScoresSubject
TaughtEnglish Lang.
Mathematics
English Lang.
Mathematics
English Lang.
Mathematics

N

Mean

39
36
39
36
39
35

46.615453.388950.2564
63.444445.0000
51.4000

Std.
Deviation
17.44407
10.88716
15.66545
23.61016
14.72735
14.91781

Std. Error
Mean
2.79329
1.81453
2.50848
3.935032.35826
2.52157

Hypothesis 2: There is no significant difference in the subject matter content knowledge
between sampled English Language and Mathematics teachers.
The F-ratio of Leven’s test of equality of variances indicated a significant difference forEnglish Language and Mathematics teachers’ subject matter content knowledge (15.712, p <0.001). There was also a significant difference between the mean of depth of subject content
knowledge of English Language and Mathematics teachers (t = -2.826, p < 0.05). Table 8 also
shows that Mathematics teachers had a significantly deeper knowledge of their subject matter.
Hypothesis 3: There is no significant difference in the performance between sampled seniorsecondary school II English Language and Mathematics students.
The Leven’s test of equality of variances revealed no significant difference in the variances ofstudents’ performance of senior secondary school II in English Language and Mathematics(0.411, p > 0.05) as shown ion Table 7. Also, no significant difference was observed in themean scores of students in English Language and Mathematics (t = -1.854, p > 0.05). Students’performance was found to be better in Mathematics than English Language.
Discussion
Findings in this study suggest that teacher training tends to have a debilitating influence on
subject content knowledge as those who obtained their degree in the same or even a related
subject to the ones they teach tend to have lower scores in the test of knowledge of subject
matter content. This may also question the observation by Abimbola (2012) that the exposure
to courses in Faculties of Education is adequate to produce competent teachers. It should be
noted that a subject in which one majors at the university level carries the heaviest weight interms of credits offered and hours spent for lectures and practical sessions. The other subjects
or courses are subsidiary and thus the hours spent receiving lectures or being exposed topractical are lower thus informing the use of major and minor to describe them. Viewed fromthis perspective therefore, the offering of education courses in the university as their major
tends to make it difficult for education students to accommodate as many courses and hours as
those of their counterparts that major in the teaching subjects like English Language andMathematics investigated in this study. At the point of graduation, those who obtained degrees
in the teaching subjects are more knowledgeable and skilled in those subjects than theircounterparts whose major is education because they have actually offered more courses andhave been exposed to more practical sessions in the subjects. The question of adequate

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Volume 6 – Issue 1 – Spring 2018knowledge comes in only when considering issues of competence to teach at the secondary
school level. What is considered adequate for use by them in teaching students needs proper
analysis.
In relation to teachers’ DPK, the results of this study generally fell in the expected direction as
the DPK of most untrained teachers was found to be weak. It is, however, surprising that a
category of untrained teachers, for example those holding the Bachelor of Science degree, still
had the most adequate depth of DPK. Though it was discovered that a few of those with a B.A.
or B.Sc. as their highest educational qualifications had earlier gone through the Nigeria
Certificate in Education (NCE) training, which is also a professional teacher qualification, thefact that the Bachelor of Science or Art in Education curriculum offers deeper professional
exposure should imply that products still perform better. Could the fact that many teachers ofEnglish Language and Mathematics might have had some measure of pedagogical knowledge
passed through specialized seminars, workshops and other training programmes, which are
regularly organized to stem the tide of mass failure in schools, have been responsible for thisunexpected result? The critical issue here is that professionally trained teachers are expected to
be clearly better and more competent in DPK. There is a problem when trained teachers andthe untrained have comparable depth of pedagogical knowledge. The exposure of the untrainedto specialized seminars and workshops may not be sufficient factor to explain this observation.
Findings in this study also indicated that teachers who had received professional training
demonstrated weaknesses in subject content and pedagogical knowledge combined with meanscores just barely half of the mark obtainable. Plausible explanation could be that these very
important skills are treated with levity when teachers start practicing thus supporting reports ofstudies by Harris and Sass (2007), Agoro and Akinsola (2013), and Ladipo, (2013), pointing
in the direction of poor quality of teachers in secondary schools. The role of teachers as
researchers may be threatened by the absence of good libraries to support their preparation for
instruction. Merely obtaining teacher’s copy of recommended textbooks and access to it cannot
be afforded in some institutions, not to talk of having access to alternative textbooks for crossreferencing, depth and balance. Reading and revising topics to be taught to students (which theteachers themselves learned many years earlier) may thus be taken for granted. Coupled withthis is the years of teaching experience during which teachers have repeatedly taught the same
topics. The teachers may then be working under the assumption that the topic is known andproceed without serious preparation. When this happens, teachers rely on residual knowledge
and thus weakens their effectiveness and delivery. This implies that the teachers may downplay
the basic principles of instruction in their preparation for the lessons they need to deliver. Amidthese, teachers of Mathematics and English Language have the tendency to have many morelessons to teach which places more demand on their time for preparation.
As expected, the subject content and pedagogical knowledge of teachers significantly predicted
students’ performance in English and Mathematics examinations. However, the variance ofstudents’ performance accounted for by both variables was found to be 10.7%. This suggested
that there are several other variables that account for students’ level of success traceable, forinstance, to the students themselves, their teachers, the school, home environments and suchother sources.
Teachers of Mathematics were observed to be having deeper pedagogical and subject matter
content knowledge. The differences in the depth of their knowledge in these two components
were found to be significant. Whereas a wider selection of graduates of related fields could feelcompetent to teach English, it is not so with Mathematics. Not many teachers are ready to86

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accept teaching Mathematics as could happen to English Language. There is therefore thetendency to have teachers from varied related fields teaching English Language but not
Mathematics.
The grand mean of students’ performance in English Language was found to be lower than thatof Mathematics. This outcome seems to be the likely combined effect of a deeper pedagogicaland subject matter content knowledge observed among teachers. It confirms the initial hunchthat informed this study and the general feeling that teachers with better knowledge of thesubject they teach will likely impact performance of students more than those with little
knowledge. The same applies to pedagogical knowledge.
Conclusions
Main Findings
1. Teachers with Bachelor of Science degrees had the deepest subject content knowledge(DSCK) with a mean of 65.42%.
2. Teachers with the most adequate depth of pedagogical knowledge (DPK) were thoseholding the Bachelor of Science degrees, with a mean of 56.08%.
3. Holders of B.Sc. degrees demonstrated the strongest DSCPK, with a mean of 121.50.
4. Sampled teachers’ depth of subject content and pedagogical knowledge significantly
predicted their students’ performance in examinations.
5. Sampled teachers of English Language were significantly weaker in terms of DPK and
DSCPK compared with teachers of Mathematics.
6. Sampled SSII students were generally better in Mathematics than English Language
although the difference in their academic performance was not statistically significant.
Implications
The overall mean score of 56.59% in DSCK showed that the sampled teachers were generally
weak. Without being strong in this skill, their competence to teach the subject is also affected.
Their delivery of instruction to learners may not be sustainable and many times, questions
raised by inquisitive and intelligent learners may not be well addressed. To probe deeper into
the causes of this low performance may require taking a look at the training received by theteachers in Faculties of Education. What is considered as adequate knowledge in their teachingsubjects and courses offered in them must be thoroughly investigated. Knowledge may be taken
for granted especially if one had gone through school and had acquired certificates or
qualifications as proof.
Also, the finding indicating that the DPK of professionally trained teachers holding B.A. Ed.
and B.Sc. Ed. fell close to the mean calls to question what happened to the teachers while intraining and after they had been certified. It also calls to question whether they are in position
to utilize their professional training while practicing in the school system. If training and skills
acquired are inadequate, delivery is weakened even before the product of such institutions
begin to work. A national study across many other school subjects should be helpful indetermining the validity of the current findings.
Limitations
A preliminary study was embarked upon to achieve the following objectives: identification of
the category of teachers (B.Ed. /B.Sc. Ed /B.A.Ed.; PGDE; or B.A. /B.Sc.) that has the deepest
DSCK; the most adequate DPK; and the strongest DSCPK. The study also investigated the87

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Volume 6 – Issue 1 – Spring 2018predictive ability of teachers’ DSCPK for students’ performance in English Language andMathematics. Seventy-eight teachers of Senior Secondary II English Language andMathematics in thirty-two randomly secondary schools in Kwara State and classes of SSII
students taught by the teachers who constituted the sample. Data were collected through tests,
observations and vignettes, patterned after Kirschner, Borowski and Fischer (2010) andBaumert et al. (2010); and analysed using descriptive and inferential statistics to compare theteachers’ DSCK /DPK/DSCPK in both subjects. Findings of the preliminary investigation
showed that teachers with B.Sc. demonstrated the deepest DSCK; the most adequate DPK; andthe strongest DSCPK. Findings of the study further indicated that both pedagogical and subject
content knowledge of sampled teachers were significant predictors of students’ success in
examinations; and the two variables accounted for 10.7% of the total variance of students’success in examinations.
However, illuminating as the findings of this study may appear, the fact that it was only apreliminary study, limited in scope and subject coverage, means that no conclusive statements
about the findings reported here can be made. Neither can the findings be taken as valid
representation of the depth of subject content and pedagogical knowledge of SSII English
Language and Mathematics teachers in Nigerian secondary schools. A large-scale national
study is therefore imperative.
Acknowledgements
The authors wish to acknowledge the roles of the following individuals:••

The secondary school English Language and Mathematics teachers involved in thedevelopment and validation of students’ academic achievement tests.
The academic staff and doctoral students of the Department of Educational
Measurement and Evaluation, University of Ilorin, Nigeria involved in the datacollection and analysis.

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Corresponding author: Felicia Olasehinde-Williams
Contact email: olabisi@unilorin.edu.ng

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