www.rsisinternational.org

Page 3395

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

Developing and Evaluating a New OJT Feedback Form: Evidence

from a Mixed-Methods Assessment of Internship Quality and

Assessment Continuity

Brenda M. Balala, MIT

, Vince Marc B. Sabado, MSIT

¹,²

Notre Dame of Marbel University, Koronadal City, Philippines Computer Studies Department

DOI:

https://doi.org/10.51583/IJLTEMAS.2026.150500277

Received: 07 June 2026; Accepted: 12 June 2026; Published: 25 June 2026

ABSTRACT

A Philippine university recently transitioned from a 10-item OJT feedback instrument to a newly developed

multidimensional OJT evaluation form designed to enhance internship assessment and quality assurance. The

last cohort of student-trainees evaluated with the old instrument: 25 Computer Studies student-trainees, 8 BSCS,

17 BSIT deployed to 10 host organizations in Region XII in Summer 2025, serves as a baseline to assess the

quality of the OJT program and the implications of this instrument change. The study provides a quantitative

benchmark and structural gaps in the new form using descriptive statistics, independent samples t-testing,

Cronbach's alpha reliability analysis, and reflexive thematic analysis of the open-ended responses. The pre-

existing instrument produced a grand mean of M = 4.63 (SD = 0.61), with scores of Supervision & Mentorship

and Workplace Environment obtaining the highest scores (both M = 4.72). The item in which training duration

adequacy was rated the lowest (M = 4.24, SD = 0.97) and the only one showing a statistically significant program

difference was rated significantly lower by the BSCS students compared to the BSIT students (M = 3.50 vs.

4.59; t(23) = −3.03, p = .006, d = −1.30, a large effect). This finding was further reinforced by four qualitative

themes: unfamiliar workplace technologies, non-existent deployment planning, delays to resource access, and

organizational constraints.

Most importantly, the revised New OJT Feedback Form instrument does not include training duration adequacy,

which was the construct with the greatest policy relevance, and does not have a holistic single item structure as

did the old instrument that allowed direct ten dimension profiling. The study sets a baseline for future assessment

and shows that the New OJT Feedback Form represents a major institutional innovation, provides greater

construct coverage, provides better qualitative feedback mechanisms and provides better support for quality

assurance and program evaluation. A key contribution of the study is the development of a revised

multidimensional OJT Feedback Form designed to support internship evaluation, quality assurance, and

evidence-based program improvement in computing education. The study suggests that the training duration

subscale be restored, that the anchors of the program comparability subscale remain the same, and that a pilot

study be conducted using the revised instrument to see how well it performs against the baseline before fully

implementing the instrument in institutions.

Keywords: OJT assessment, internship evaluation, work-integrated learning, computing education, feedback

instrument development, program evaluation, quality assurance, internship satisfaction, higher education,

Philippines

INTRODUCTION

Many of the methodological implications of instrument transitions in institutional program evaluation come with

great stakes, as they can broaden the construct coverage, enhance the theoretical foundations, and yield richer

data, but also risk compromising the longitudinal comparability, missing key dimensions, and creating blind

spots in the assessment. During the Second Semester of Academic Year 2025–2026, a participating university's

computing education program transitioned from a 10-item OJT Feedback Form to a newly developed

multidimensional OJT Feedback Form designed to enhance assessment quality and program evaluation.

www.rsisinternational.org

Page 3396

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

This study has employed the last cohort evaluated on the pre-existing old feedback form as an empirical baseline

to inform understanding of what was already captured by the pre-existing instrument, what is preserved and

extended by the new instrument and what is missing. The 25 student-trainees who finished the old form offer a

unique transition dataset, in that their answers will give the final, fully comparable most recent observation point

pre-change of instrument, and the qualitative stories they tell will explain aspects that the old form could not

quantify.

The difference in perceived training duration adequacy between BSCS and BSIT students is statistically

significant and also practically large (t(23) = −3.03, p = .006, d = −1.30) and this dimension is not captured by

the New OJT Feedback Form, therefore the transition is substantively important. This paper proposes that this

omission needs to be acknowledged, measured and discussed before the new instrument becomes

institutionalized.

The study thus serves two concurrent purposes: (1) it assesses the quality of the OJT in Summer 2025, via the

validated instrument and (2) it maps the structural similarities and differences between the old and new forms to

guide decisions on instrument adoption based on evidence (Luk & Chan, 2024; Gutiérrez-Pulido & Orozco-

Rodríguez, 2025).

Research Objectives

The Objectives of This Study Were to:

1. Create Baseline Measures for OJT Quality for the Summer 2025 Cohort Across the Ten Evaluation

Dimensions of the Old Feedback Form; and

2. Compare and Contrast Program-Level Differences (BSCS vs. BSIT) in OJT Satisfaction Specifically

With Respect to Training Duration Adequacy; and

3. Identify Preserved, Expanded and Missing Constructs Between the Old 10 Item Old Feedback Form and

the New 28 Item, 6 Subscales New OJT Feedback Form; and

4. Make Evidence-Based Recommendations to Finish Instrument Transition Without Loss of Benchmarks

Set Forth by Past Cohort.

REVIEW OF RELATED LITERATURE

Theoretical Framework: Experiential Learning Theory

This study is based on Kolb's (1984) theory of Experiential Learning Theory (ELT) that is a four-stage learning

process consisting of concrete experience, reflective observation, abstract conceptualization, and active

experimentation. Applied to OJT contexts, ELT signifies that effective workplace learning needs to be given

adequate amount of time, guided reflection and planned opportunities for applying understanding. Shortened

training times, especially in more technical fields, can break this cycle. In particular, this theoretical perspective

is directly applicable to the study's key finding that the training duration adequacy is structurally mismatched

with BSCS program demands, which is why the omission in the new OJT Feedback form is a theoretically

significant one (Gandhi & Kuknor, 2024).

Work-Integrated Learning and OJT Instrument Design

Work-integrated learning (WIL) refers to internships, practica and cooperative education that place learning in

the context of professional workplaces (Curto-Reverte et al., 2025). Data from program assessment is valid and

useful based on the quality of the evaluation instruments used to assess WIL. Luk and Chan (2024), in their

systematic review of WIL assessment methods, highlight four uses of assessment: to ensure learning, to improve

learning, to fulfil accountability and to facilitate student development. A dismissal of a dimension that serves

one or more of these purposes (particularly accountability) must be based on empirical evidence.

The authors Gutiérrez-Pulido and Orozco-Rodríguez (2025) find that validated OJT instruments used in

engineering and computing practica are most effective when they are organized into a theorized set of subscales,

www.rsisinternational.org

Page 3397

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

feature both Likert and open-ended items, and align the constructs of the instruments with the program learning

outcomes. The New OJT Feedback Form is a change from 10 holistic items to 28 items organized by subscales,

which aligns with these recommendations, but will need to be validated against the previous data to ensure

construct fidelity (Ferns et al., 2024).

Indeed, the importance of the technical and professional competency dimensions in the evaluation of OJT has

been emphasized in recent studies (Franco-Ángel et al., 2023), as well as the quality of the supervisor and

mentoring system which has been identified as the most important factors determining learning outcomes within

WIL (Jackson & Dean, 2023; Schneider et al., 2024).

Training Duration as a Critical Assessment Dimension

A dimension that has not been sufficiently studied in higher education in the Philippines is the length of OJT

training. In a systematic review article on research studies of WIL intervention, Hwang et al. (2026) report that

long-term workplace exposure is consistently linked with increased depth of learning and enhanced professional

readiness. In computer-related fields, this has been complicated by the fact that work in software development,

systems analysis, and database design is iterative, meaning that these processes cannot easily be compressed into

short timeframes (ACM & IEEE Computer Society, 2020).

This current study's result of a large preponderance of a statistically significant BSCS-BSIT difference in the

training duration satisfaction (d = −1.30) is directly relevant to this literature and offers empirical support that

training duration should be an explicit evaluative construct in successor instruments. Unfortunately, it is not only

a coverage gap, but also a theoretical concern, and needs to be addressed immediately.

METHODS

Research Design

This study employed a mixed-methods descriptive-evaluative research design. The quantitative strand relies on

descriptive statistics, reliability analysis, and group comparison for inferential analysis to describe and provide

baseline metrics for trainee perceptions for the Summer 2025 cohort. For the qualitative strand, the reflexive

thematic analysis (Braun & Clarke, 2022) was used to identify themes that are common to the trainee's narratives

and to give meaning to quantitative findings. A second analytical strand performs a structured comparison of the

Old Feedback Form and the New OJT Feedback Form, and charts item level continuities and discontinuities.

The design is based on the evaluative research with small, well-defined populations recommended by Creswell

and Creswell (2023).

Participants and Sampling

The study sample consisted of all 25 student-trainees who are enrolled in the computer education program of the

participating university for the Summer 2025 period of OJT/Practicum. Because the population was small and

the entire population was accessible, complete census sampling was employed. The study therefore captured

100% of the eligible Summer 2025 OJT cohort, eliminating sampling error within the target population and

providing a complete institutional baseline for program evaluation. While the findings are not intended for broad

statistical generalization beyond the participating university, they offer a comprehensive and internally valid

assessment of the entire trainee cohort. Of the 25 participants, 8 (32%) were enrolled in BSCS and 17 (68%) in

BSIT. These participants were spread out among 10 host organizations: Provincial Government of South

Cotabato (PGSouth Cotabato) (n = 7), DICT South Cotabato (n = 3), DEPDev Regional Office XII (n = 3), Lead

Solutions Inc. (n = 3), Dole Philippines Inc. (n = 2), and four single-placement organizations: Unicenter

Communications, SOCOTECO I, City Government of Koronadal, Philippine Coconut Authority Region 12. 25

participants provided full answers.

Instruments

The main data source for this study was the official OJT evaluation instrument used by the computing education

program in Summer 2025, which is the Computer Studies Program Course Satisfaction old feedback form. The

www.rsisinternational.org

Page 3398

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

instrument was composed of the 10 Likert-type items on a five point scale from 1 (Strongly Disagree) to 5

(Strongly Agree) and two open-ended response fields with questions about problems encountered and other

concerns about the internship experience. The 10 items evaluated major aspects of the OJT quality: Program-

academic alignment, supervisory support, task relevance, access to resources, technical skill development,

communication and interpersonal skills, constructive feedback, training duration adequacy, confidence in real-

world application, satisfaction and recommendation. The current data set was found to have a high internal

consistency with a Cronbach's alpha coefficient of α = .892.

Results from the analysis of the old feedback instrument were used to inform assessment continuity and to

develop a revised internship assessment tool. In particular, item-level results, reliability evidence, and qualitative

feedback themes were utilized to identify the constructs that need to be retained, expanded, revised, or created

in a revised assessment framework. Specific focus was placed on dimensions with high practical significance,

including training duration adequacy, supervisory support, resources at the workplace and professional skill

development.

Based on this evaluation process, the study proposes the New OJT Feedback Form as a revised assessment tool

for subsequent validation and institutional implementation, and as the principal research output of the study.

This re-designed instrument is now 28 items across six theoretically based dimensions: (1) Quality of Learning

Experience, (2) Supervision and Mentorship, (3) Workplace Environment, (4) Skills Development, (5) Program

and Company Alignment, and (6) Overall Internship Experience. The new form has five quality levels (from 1

for Poor to 5 for Excellent), includes structured trainee profiling information (such as program name, year level,

training hours, industry sector, task type, and supervisor information), and eliminates the two open-ended

narrative questions in favor of four focused feedback questions concerning learning experiences, internship

challenges, company enhancement, and recommendations for strengthening the university’s OJT program.

The instrument was redesigned to give a wider range of constructs, a stronger connection to current WIL

assessment practices, more information in the qualitative section, and better support for institutional quality

assurance, program evaluation, accreditation, and ongoing curriculum development. Therefore, the Old

Feedback Form served as the primary data collection instrument for this study, while the New OJT Feedback

Form constitutes the principal assessment innovation and practical research output resulting from the study.

INSTRUMENT COMPARISON METHODOLOGY

Construct mapping was conducted by (a) listing all items from both instruments, (b) identifying conceptual

alignments between old items and new subscale categories, (c) flagging constructs present in the old form but

absent in the new form, and (d) identifying new constructs in the New OJT Feedback Form with no old-form

antecedent. This analysis followed the construct coverage framework proposed by Luk and Chan (2024) and

was cross-validated against the subscale structure reported by Gutiérrez-Pulido and Orozco-Rodríguez (2025).

Data Analysis

Quantitative data were analyzed using descriptive statistics (means, standard deviations, frequency distributions)

and Cronbach’s alpha reliability coefficients. An independent samples t-test was conducted to compare BSCS

and BSIT students on Q8 (training duration adequacy), with effect size quantified using Cohen’s d (Cohen,

1988). Assumptions of normality and homogeneity of variance were confirmed using the Shapiro–Wilk and

Levene’s tests (Field, 2018). All quantitative analyses were conducted in Python using NumPy and SciPy.

Qualitative data were analyzed using Braun and Clarke’s (2022) six-phase reflexive thematic analysis

framework.

Research Ethics

Permission to conduct the study was obtained from the computing education program of the participating

university. Participation was voluntary, and all student-trainees were informed of the purpose of the study prior

to data collection. Responses were treated confidentially, and all data were analyzed and reported in aggregate

form to protect participant anonymity. No personally identifiable information was included in the analysis or

www.rsisinternational.org

Page 3399

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

dissemination of findings. The study utilized existing program evaluation data solely for academic research and

quality assurance purposes and complied with institutional ethical standards for educational research.

RESULTS

Instrument Comparison: Old Feedback Form vs. New OJT Feedback Form

Table 1 presents a systematic construct map comparing the 10 items of the old feedback form against the six

subscales of the New OJT Feedback form. Each old item is classified as: Preserved (a new item directly captures

the same construct), Expanded (the new form extends the construct across multiple items), or Absent (no new

item captures the construct).

Table 1

Construct Map: Old Feedback Form vs New OJT Feedback Form

Item

Old Feedback Form

New OJT Feedback Form

Corresponding Subscale

New Items Aligned

Status

Program-academic

alignment

Program & Company

Alignment (4 items)

Tasks relevant to the program;

Internship met expectations

Expanded

Mentorship and

supervisory support

Supervision & Mentorship (5

items)

Supervisor approachable;

Adequate guidance; Improve

professional skills

Expanded

Task relevance and

meaningfulness

Program & Company

Alignment / Quality of

Learning (dual mapping)

Tasks contributed to

professional learning;

Meaningful training activities

Expanded

Access to resources and

tools

Workplace Environment (5

items)

Sufficient resources; Positive

environment; Safety and

comfort

Expanded

Technical skill

development

Quality of Learning Experience

/ Skills Development (dual

mapping)

Develop new technical skills;

Problem-solving improved

Expanded

Communication and

interpersonal skills

Skills Development (5 items)

Communication improved;

Teamwork developed

Expanded

Constructive

performance feedback

Supervision & Mentorship (5

items)

Constructive feedback on work

performance

Preserved

Training duration

adequacy ⚠

— No corresponding subscale

—

None identified in any subscale

ABSENT

Confidence in real-

world application

Skills Development / Quality of

Learning (dual mapping)

Gained confidence in

professional responsibilities;

Employment readiness

Expanded

Q10

Overall satisfaction and

recommendation

Overall Internship Experience

(3 items)

Overall satisfied; Recommend

company; Grew professionally

Expanded

Note. ⚠ Q8 (Training Duration Adequacy) is the only old-form construct with no counterpart in the New OJT

Feedback From. It was also the item with the lowest mean (M = 4.24) and the only item demonstrating a

www.rsisinternational.org

Page 3400

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

statistically significant program difference (BSCS vs. BSIT, p = .006, d = −1.30). Shaded row indicates an

unresolved assessment gap.

As shown in Table 1, nine of ten old-form constructs are either preserved or expanded in the New OJT Feedback

form. The most notable additions in the new form include Workplace Environment items (professional treatment,

team culture, safety/comfort) and structured open-ended prompts that replace the old form’s unstructured fields.

The sole missing construct is Q8 (Training Duration Adequacy), which, given its role as the study’s primary

inferential finding, represents the most consequential gap in the instrument transition.

Scale and Response Format Changes

The old feedback form used a strongly disagree–strongly agree (SD–SA) scale for all items. The New OJT

Feedback form shifts to a Poor–Excellent (1–5) scale. This change has implications for response distribution

comparability: the SA–SD format anchors responses to agreement with descriptive statements, while the Poor–

Excellent scale anchors to quality evaluation. Evidence of response scale effects indicates that such a change

may affect the distributional characteristics of the responses ratings even if substantive attitudes remain constant

(Creswell & Creswell, 2023).

The change necessitates that baseline data from the old form be recalibrated before use as thresholds when

interpreting results from the new form, for use in a longitudinal comparison. The two open-ended questions

(Problems Met; Other Concerns) in the old form are no longer open-ended but rather are structured in the new

form. While this helps to improve how easily the qualitative feedback is actionable (structured prompts result in

more topic specific, codable responses than open fields, Braun & Clarke, 2022), it also has the disadvantage that

the themes found in the old form will not be directly comparable to the responses in the new form.

Baseline Old Feedback Form

Table 2 presents item-level descriptive statistics for the Summer 2025 cohort, providing the empirical baseline

against which future New OJT Feedback Form results should be benchmarked.

Table 2 Baseline Descriptive Statistics, Old Feedback Form (N = 25)

Item

Construct

Min

Max

Interpretation

Program-academic alignment

4.56

0.65

Strongly Agree

Mentorship and supervisory support

4.72

0.46

Strongly Agree

Task relevance and professional development

4.68

0.56

Strongly Agree

Access to resources and tools

4.72

0.54

Strongly Agree

Technical skill development

4.68

0.56

Strongly Agree

Communication and interpersonal skills

4.64

0.57

Strongly Agree

Constructive performance feedback

4.72

0.46

Strongly Agree

Q8*

Training duration adequacy ⚠

4.24

0.97

Agree

Confidence in real-world application

4.68

0.56

Strongly Agree

Q10

Overall satisfaction & recommendation

4.64

0.57

Strongly Agree

Grand

Overall (all 10 items)

4.63

0.61

—

Strongly Agree

www.rsisinternational.org

Page 3401

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

Note. Scale: 4.50–5.00 = Strongly Agree; 3.50–4.49 = Agree. ⚠ Q8* (shaded) is absent from the New OJT

Feedback Form. Cronbach's α = .892 for the full 10-item scale; all alpha-if-deleted values fell below the overall

coefficient.

Subscale-Level Analysis: Old Form Items Mapped to New Form Categories

To facilitate prospective comparison with future New OJT Feedback Form data, Table 3 presents subscale-level

means computed by grouping old-form items according to their closest corresponding new-form subscale. This

mapping establishes provisional benchmarks against which New OJT Feedback Form subscale results may be

compared, subject to the scale-format caveat noted in Section 4.2.

Table 3 Subscale-Level Baseline Statistics (Old Items Mapped to New Form Categories, N = 25)

New Form Subscale

Old Items

Mapped

Overall

BSCS M

BSIT M

Diff

Quality of Learning Experience

Q1, Q3, Q5, Q9

4.65

0.58

4.62

4.66

−0.04

Supervision & Mentorship

Q2, Q7

4.72

0.45

4.75

4.71

+0.04

Workplace Environment

4.72

0.54

4.75

4.71

+0.04

Skills Development

Q5, Q6, Q9

4.67

0.55

4.62

4.69

−0.06

Program & Company Alignment

Q1, Q3

4.62

0.60

4.62

+0.01

Overall Internship Experience

Q10

4.64

0.57

4.38

4.76

−0.39

Training Duration [ABSENT ⚠]

Q8 only

4.24

0.97

3.50

4.59

−1.09*

Note. Diff = BSCS minus BSIT mean. * p = .006, two-tailed t-test, Cohen's d = −1.30 (large effect). Shaded row

indicates a dimension absent from the New OJT Feedback Form. Items used in multiple subscale mappings (Q1,

Q3, Q5, Q9) reflect overlapping construct coverage in the new form.

As shown in Table 3, the largest BSCS–BSIT difference is concentrated in the Training Duration subscale (Diff

= −1.09), which corresponds exclusively to Q8 in the old form. All other subscale differences are negligible (≤

0.39 points). This pattern reinforces the conclusion that the BSCS–BSIT disparity is not a general satisfaction

gap but a specific, structurally grounded concern about training time sufficiency for project-intensive computing

work.

Statistical Reliability of the Old Instrument

Table 4 presents item-level variance and alpha-if-deleted statistics for the old feedback form 10-item scale,

confirming the reliability of the baseline data.

Table 4 Item Reliability Statistics, Old Feedback Form (N = 25, k = 10, Overall α = .892)

Item

Construct

Variance (σ²)

α if Deleted

Status

Program-academic alignment

0.42

0.877

Contributes to scale

Mentorship and supervisory support

0.21

0.875

Contributes to scale

Task relevance

0.31

0.880

Contributes to scale

www.rsisinternational.org

Page 3402

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

Resource access

0.29

0.880

Contributes to scale

Technical skill development

0.31

0.889

Contributes to scale

Communication skills

0.32

0.891

Contributes to scale

Constructive feedback

0.21

0.890

Contributes to scale

Q8*

Training duration adequacy ⚠

0.94

0.888

Highest variance; still contributes

Real-world confidence

0.31

0.871

Contributes to scale

Q10

Overall satisfaction

0.32

0.875

Contributes to scale

Note. ⚠ Q8* exhibits the highest item variance (σ² = 0.94), yet removing it lowers overall α from .892 to .888,

confirming that its high variance reflects genuine construct heterogeneity rather than measurement error. All

alpha-if-deleted values are below the overall coefficient.

Program Comparison (BSCS vs. BSIT): Full Item Matrix

Table 5 presents the complete program-level comparison across all ten items.

Table 5 Item-Level Means by Program: BSCS (n = 8) vs. BSIT (n = 17)

Item

Construct

BSCS M (SD)

BSIT M (SD)

Diff

t (df=23)

Program-academic

alignment

4.38 (0.74)

4.65 (0.61)

−0.27

—

Mentorship support

4.75 (0.46)

4.71 (0.47)

+0.04

—

Task relevance

4.88 (0.35)

4.59 (0.62)

+0.29

—

Resource access

4.75 (0.71)

4.71 (0.47)

+0.04

—

Technical skills

4.62 (0.52)

4.71 (0.59)

−0.09

—

Communication skills

4.62 (0.52)

4.65 (0.61)

−0.03

—

Constructive feedback

4.75 (0.46)

4.71 (0.47)

+0.04

—

Q8*

Training duration ⚠

3.50 (1.07)

4.59 (0.71)

−1.09

−3.03

.006**

Real-world confidence

4.62 (0.52)

4.71 (0.59)

−0.09

—

Q10

Overall satisfaction

4.38 (0.74)

4.76 (0.44)

−0.38

—

Note. Diff = BSCS minus BSIT mean difference. ** p < .01, two-tailed t-test, Cohen's d = −1.30 (large effect).

Only Q8 was subjected to formal t-testing as the pre-specified primary comparison. ⚠ Q8* is absent from the

New OJT Feedback Form.

Qualitative Findings: Thematic Analysis of Open-Ended Responses

Braun and Clarke's (2022) six-phase reflexive thematic analysis was used to examine open-ended responses from

the Problems Met field (16 of 25 respondents, 64%) and Other Concerns field (5 of 25). Each of the four recurring

motifs has a direct bearing on the instrument transition.

www.rsisinternational.org

Page 3403

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

Theme 1: Unfamiliar Workplace Technologies Requiring Rapid Self-Directed Adaptation. Experiencing

enterprise tools—Crystal Reports, ASP.NET MVC, React Native, Microsoft SharePoint, and PowerApps—that

are not included in the curriculum was the most commonly mentioned difficulty. This theme is captured in the

new form's Quality of Learning Experience subscale and the challenges open-ended prompt, making it a

construct well-served by the New OJT Feedback Form transition. One BSCS trainee reported that having to

"explore and study [an unfamiliar programming language] from scratch" caused "slow progress" and made the

training period "feel a bit short."

Theme 2: Absent Deployment Planning and Shifting Task Assignments. Many respondents stated that "a

lack of a fixed OJT plan" resulted in "abrupt changes in tasks" and made it impossible to monitor progress. This

theme maps to the Program & Company Alignment subscale in the new form, specifically the item “The

internship met my expectations.” The new form’s structured question on company improvement suggestions

would elicit this feedback more directly than the old form’s open Problem field.

Theme 3: Resource and Equipment Access Gaps. One respondent mentioned interdepartmental signature

delays, while two reported equipment delays (waiting days for a company device). Compared to the old form's

single Q4 item, the new instrument's differentiated subscale structure better captures these, which correspond to

the Workplace Environment subscale ("The company provided sufficient resources").

Theme 4: Structural and Organizational Constraints Amplifying Duration Inadequacy. Many BSCS

trainees claimed that organizational needs—such as the absence of databases, ambiguous criteria at the beginning

of training, and frequent elicitation meetings—were consuming training time without actually having any

impact. "With no existing database, the work of system design had to start from scratch," according to a

Philippine Coconut Authority trainer. The New OJT Feedback Form does not include information on training

time because it is not a part of the form. The largest unbridgeable alignment gap between the two instruments is

this one.

The alignment summary for the new form is open-ended. Three themes of qualitative data (unfamiliar

technology, lack of preparation, and resource gaps) are well reflected in the new form's subscale items and

structured open-ended items. The fourth subject, the structural limitations that worsen the inadequate duration,

has no equivalent item in the new form. With the exception of the length dimension, the four structured questions

on the new form constitute a significant addition to the two unstructured question sections from the prior version.

DISCUSSION

The New Form Expands Coverage on Nine of Ten Constructs

The New Form contains a real methodological improvement, with the expansion of 9 of 10 constructs on 6

theoretically grounded subscales of the New OJT Feedback form. Previously assessed constructs are now

evaluated on several related facets: Workplace Environment is assessed by a 5 item subscale that also includes

access to resources (Q4); Supervision & Mentorship is assessed by a 5 item subscale that also includes a measure

of supervisory support (Q2, Q7). This multidimensional structure yields more granular diagnostics, allows for

subscale-level reliability analysis and meets best-practice recommendations for the computation and engineering

practicum evaluation (Gutiérrez-Pulido & Orozco-Rodríguez, 2025; Luk & Chan, 2024). The new form also has

4 well-defined open-ended questions as opposed to 2 unstructured questions in the previous version. Structured

prompts elicit more codable, actionable narratives (Braun & Clarke, 2022), and the specific prompts for

suggestions for company improvement and suggestions for institutional program improvement.

The Critical Missing Dimension: Training Duration Adequacy

The most consequential finding of the instrument comparison concerns Training Duration Adequacy. Among all

ten items in the Old Feedback Form, this construct obtained the lowest mean score (M = 4.24), exhibited the

highest variance (σ² = 0.94), and was the only item that revealed a statistically significant difference between

BSCS and BSIT students (d = −1.30). These findings suggest that perceptions of internship duration vary

substantially across computing programs and represent a meaningful dimension of internship quality. Because

www.rsisinternational.org

Page 3404

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

no corresponding item exists in the New OJT Feedback Form, the transition introduces a potential assessment

gap that may limit future monitoring of program-specific internship needs.

A possible explanation for the observed difference is the nature of BSCS training requirements. Compared with

BSIT programs, BSCS internships frequently involve project-based activities such as software development,

database design, systems analysis, and application development, which require iterative cycles of planning,

implementation, testing, and refinement. These activities often demand longer periods of workplace immersion

before meaningful project completion can occur. In contrast, BSIT placements may involve more operational,

support-oriented, or infrastructure-related tasks that can be completed within shorter training periods.

Consequently, perceptions of insufficient training duration among BSCS trainees may reflect structural

differences in internship complexity rather than differences in overall internship quality.

The policy relevance of this finding extends beyond measurement concerns. Existing practicum hour

requirements are typically applied uniformly across computing programs, yet the present findings indicate that

BSCS students may require longer workplace immersion than BSIT students. Retaining a Training Duration

Adequacy indicator would therefore provide institutions with evidence necessary for evaluating whether current

practicum requirements remain appropriate across different computing disciplines.

Response Scale Change and Longitudinal Comparability

This change in scale from Agree–Disagree (SD–SA) to Poor–Excellent (1–5) creates an inherent translation error

and restricts cross cohort score comparisons. The old form was used where everything was stated in a positive

way that wouldelicit assent. In the new form, items are worded as criteria upon which the quality of items is

judged. Both scales range from 1-5, but the psychological meaning is different. Ratings on the old form are

indicative of the extent of agreement with positive OJT experiences while ratings on the new form are indicative

of qualitative judgment of program excellence. It should be noted that mean scores of the baseline cohort should

not be used directly as benchmarks for new-form scores.

This comparability challenge is often seen in the transitions between the different instruments in institutional

research (IR) work (Creswell & Creswell, 2023) and does not mean the transition is invalidated, it simply means

that the first cohort in the New OJT Feedback Form should be analyzed separately from the second cohort before

any cross-cohort trends are interpreted. Before reporting longitudinal change, the Department is advised to do a

short parallel administration or anchor-item study to set a conversion point.

The New OJT Feedback Form as the Principal Output of the Study

While This Study Helps to Set the Baseline OJT Quality Metrics, One of the Key Findings of This Research Is

the Development and Enhancement of the New OJT Feedback Form as an Improved Assessment Tool for

Computing Practicum Programs. The New OJT Feedback Form Is a Theoretically Enhanced Assessment

Framework That Expands Construct Coverage and Aligns More Closely With Contemporary Work-Integrated

Learning Assessment Practices. However, Its Psychometric Performance Remains to Be Established Through

Future Validation Studies, Over the Previous Instrument That Only Assessed Ten Separate Indicators, as It Now

Includes Twenty-Eight Items Across Six Theoretically Based Dimensions: Quality of Learning Experience;

Supervision and Mentorship; Workplace Environment; Skills Development; Program and Company Alignment;

and Overall Internship Experience.

The New Instrument Overcomes Some of the Weaknesses of the Previous Version. First, It Increases the

Construct Representation by Using the Multiple Indicators for Each Major Dimension, Which Will Increase the

Diagnostic Value and Provide for Further Reliability and Validity Analyses. Second, the Presence of Variables

That Characterize the Trainees' Profile (E.G., Program, Year Level, Training Hours, Industry Sector, Task Type,

Information About the Supervisors) Allows for More Detailed Subgroup Analyses and Evidence-Based Program

Evaluation. Third, the Substitution of Two Narrative Fields With Four Focused Feedback Questions Enhances

the Quality, Specificity and Actionability of Qualitative Data Obtained From Trainee Respondents.

www.rsisinternational.org

Page 3405

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

The Instrument Is Also Based on Recent Research in the Field of Work-Integrated Learning Assessment, Which

Focuses on Assessment Practices That Are Multidimensional, That Enable Competency Development, That

Provide Quality Workplace Learning, and That Involve Mechanisms for Feedback From Those Who Are

Involved. Therefore, the New OJT Feedback Form Can Be Used as a Quality-Assurance Instrument That

Provides Evidence for Curriculum Improvement, Internship Partnership Evaluation, Accreditation Activities,

and Policy Development, as Well as an Institutional Evaluation Instrument.

Although the Revised Instrument Demonstrates Stronger Construct Coverage and Improved Assessment

Structure, Future Validation Efforts Should Also Examine Whether Important Dimensions Identified in the

Baseline Assessment, Particularly Training Duration Adequacy, Warrant Inclusion in the Final Instrument

Design. Future Research Should Subject the New OJT Feedback Form to Pilot Implementation, Reliability

Testing, Exploratory Factor Analysis, and Confirmatory Factor Analysis to Establish Content Validity, Construct

Validity, and Measurement Reliability Across Multiple Cohorts and Institutional Contexts.

Beyond Addressing Assessment Gaps, the New OJT Feedback Form Represents an Advancement in Internship

Evaluation Because It Provides Multidimensional Measurement, Richer Trainee Profiling Data, and Structured

Qualitative Feedback. These Enhancements Allow Institutions to Move Beyond Overall Satisfaction Ratings

Toward More Evidence-Based Program Improvement and Quality Assurance Practices.

CONCLUSION AND RECOMMENDATIONS

Conclusion

This study established baseline OJT quality indicators using the final cohort assessed with the previous feedback

instrument and examined the implications of transitioning to a revised multidimensional OJT Feedback Form.

The results indicate high overall program satisfaction (M = 4.63) and that BSCS students, on average, had a

large training duration gap (d = −1.30) while the students in Summer 2025 had high satisfaction with their

supervisory and resource support. One of the important outcomes of the instrument transition is that the

constructs which are empirically important from the baseline instrument must be retained, especially the

constructs related to the internship experiences in a program. The response scale change is not only significant,

but also limited in its ability to directly compare to the mean over the years without a recalibration.

Based on this study, this study has developed revised assessment framework — New OJT Feedback Form to

improve assessment, quality assurance and program improvement in internship. The instrument has good

coverage in theoretical aspects and further validation study needs to be conducted to determine the validity of

the instrument in a psychometric aspect. The revised instrument offers a more comprehensive measure of

construct coverage, greater consistency with current WIL frameworks, enhanced qualitative feedback

mechanisms, and more detailed contextual information for institutional decision making, compared to the

previous instrument. Thus the instrument is a practical research output which could be used for ongoing

improvement, program monitoring and evidence-based educational planning.

Recommendations

Based on the convergent quantitative and qualitative evidence, the following recommendations are offered:

Recommendation 1: Institutional Adoption and Refinement of the New OJT Feedback Form. The new

OJT Feedback Form is recommended as the main assessment tool for students-trainees due to its wider construct

coverage, more effective assessment structure, better qualitative feedback systems, and more relevance to current

assessment systems for work-based learning. However, before full implementation, a dimension to reflect the

most important construct found in the present study, Training Duration Adequacy, should be added.

Recommendation 2: Retain Response Scale Anchors for Transitional Comparability. The program

administrators should include one or two anchor items with the previous SA-SD scale as anchor items in the first

two cohorts in the New OJT Feedback Form to ease empirical calibration of the scale difference. This will retain

the advantages of the new form whilst allowing for trend reporting on a longitudinal basis.

www.rsisinternational.org

Page 3406

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

Recommendation 3: Use This Study’s Subscale Benchmarks as Provisional Thresholds. Institutions

implementing the New OJT Feedback Form should compare their subscale results against the baseline statistics

reported in Table 3, while acknowledging differences in response scale formats.

Recommendation 4: Implement Pre-Deployment Tripartite Agreements. Pre-deployment coordination is

the most practical lever for improving OJT, according to qualitative themes 2 and 4 (missing deployment

preparation; organizational limitations compounding length insufficiency). An organized Memorandum of

Agreement with weekly learning objectives, required tools, equipment provision timelines, and project scope

should be executed before a student’s first day of training.

Recommendation 5: Review Program-Specific Practicum Hour Requirements. The observed BSCS–BSIT

difference in perceived training duration adequacy suggests that uniform practicum-hour requirements may not

fully accommodate the learning demands of different computing disciplines. Institutions and policymakers

should evaluate whether program-specific internship requirements are warranted.

Limitations and Future Research

Limitations of the Study

The Results Presented in This Thesis Have Limitations and Point to Directions for Future Research.

There Are Four Main Limitations to This Study. The First Is That the Sample (N = 25) Is Restricted to a Single

University, Which Restricts the Generalizability of the Results to Other Institutions. The Study, However, Was

Conducted by Complete Population Sampling in Order to Have a Complete Institutional Baseline Without

Sampling Error in the Population Under Study as It Includes All 100% of the Target Population. Second, the

Study Relies Solely on Student Self-Report Data on the Old Form, and Construct Validity Could Be Enhanced

by Combining Student Self-Report Data From the Old Form With Supervisor Evaluation Data From the New

Form. Thirdly, a Formal Concurrent Validity Investigation Is Necessary Due to the Lack of Empirical

Equivalency Testing to Perform a Comparison of the Instruments Based on Content Analysis. Fourth, the

Empirical Data for the New Cohort Is Not Available on the New OJT Feedback Form, Thus Transition Effects

Cannot Yet Be Quantified Empirically. Further Research Should Conduct a Cross-Cohort Comparison, With

Formal Scale Calibration and Anchor Items, for Robust Long-Term Comparison After the First Full Cohort Is

Available.

Last, the Proposed New OJT Feedback Form Has Not Been Empirically Validated Via Pilot Implementation,

Tested for Reliability, and Factor Analyzed. Thus, Its Measurement Effectiveness and Psychometric Superiority

Are Tentative Until Future Validation Studies to Confirm It.

Multi-Institutional Validation Studies Involving Computing and Non-Computing Disciplines Are

Recommended to Determine the Generalizability and Construct Stability of the Proposed Instrument Across

Different Educational Contexts.

REFERENCES

1. Association for Computing Machinery & IEEE Computer Society. (2020). Computing curricula 2020:

Paradigms for global computing education. ACM.

https://doi.org/10.1145/3467967

2. Bisschoff, Z. S., & Massyn, L. (2025). A conceptual soft skills competency framework for enhancing

graduate intern employability. Higher Education, Skills and Work-Based Learning, 15(7), 66–81.

https://doi.org/10.1108/HESWBL-08-2023-0239

3. Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. SAGE Publications.

4. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum

Associates.

5. Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods

approaches (6th ed.). SAGE Publications.

www.rsisinternational.org

Page 3407

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026

6. Curto-Reverte, N., Mir-Marin, J., Gisbert-Soler, V., & Merigó, J. M. (2025). The role of work-integrated

learning in the European Higher Education Area: A systematic review. Review of Education, 13(1).

https://doi.org/10.1002/rev3.70114

7. Di Meglio, G., Barge-Gil, A., Camiña, E., & Moreno, L. (2022). Knocking on employment's door:

Internships and job attainment. Higher Education, 83(1), 137–161. https://doi.org/10.1007/s10734-020-

00643-x

8. Di Pietro, G. (2022). International internships and skill development: A systematic review. Review of

Education, 10(1), Article e3363. https://doi.org/10.1002/rev3.3363

9. Ferns, S., Zegwaard, K. E., Pretti, T. J., & Rowe, A. D. (2024). Defining and designing work-integrated

learning curriculum. Higher Education Research & Development. Advance online publication.

https://doi.org/10.1080/07294360.2024.2399072

10. Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.

11. Franco-Ángel, M., Carabali, J., & Velasco, M. I. (2023). The internship performance of undergraduate

students: Are hard or soft skills more important? Industry and Higher Education, 37(3), 384–396.

https://doi.org/10.1177/09504222221127213

12. Gandhi, A., & Kuknor, S. (2024). The potential of virtual internships for management education:

Capturing student journey through experiential learning. Education + Training, 66(2/3), 341–354.

https://doi.org/10.1108/ET-03-2022-0116

13. Gutiérrez-Pulido, H., & Orozco-Rodríguez, C. (2025). The contribution of professional internships to the

academic development of engineering and science students: A case study. Frontiers in Education, 10,

Article 1563361. https://doi.org/10.3389/feduc.2025.1563361

14. Hwang, A. L., Bhattacharya, M., & Baehr, J. (2026). Systematic review of work-integrated learning in

undergraduate engineering education. Journal of Engineering Education, 115(1).

https://doi.org/10.1002/jee.70050

15. Jackson, D., & Dean, B. A. (2023). The contribution of different types of work-integrated learning to

graduate employability. Higher Education Research & Development, 42(1), 93–110.

https://doi.org/10.1080/07294360.2022.2048638

16. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice-

Hall.

17. Luk, S. Y. Y., & Chan, C. K. Y. (2024). Assessing student learning in work-integrated learning (WIL): A

systematic review on assessment methods and purposes. Teaching and Teacher Education, 141, Article

104506.

https://doi.org/10.1016/j.tate.2024.104506

18. Musa, S., Nurhayati, S., & Boriboon, G. (2025). The effect of internships on graduates' employability, soft

skills, and digital competence. Educational Process: International Journal, 17, Article e2025306.

https://doi.org/10.22521/edupij.2025.17.306

19. National Association of Colleges and Employers. (2023). Internship and co-op survey report. NACE

Center for Career Development and Talent Acquisition. https://www.naceweb.org

20. Salgarayeva, G., Bazarbayeva, A., & Smyrnova-Trybulska, E. (2026). Research on the opinion of

employers on skills and conditions of their development based on courses and internships of IT graduates.

Industry and Higher Education. Advance online publication. https://doi.org/10.1177/09504222261423343

21. Schneider, B., Dittrich, C., Schmitt, C., Haberstroh, J., & Kiesewetter, J. (2024). Creating better internships

by understanding mentor challenges: Findings from a series of focus groups. International Journal of

STEM Education, 11, Article 60. https://doi.org/10.1186/s40594-024-00518-y

22. Succi, C., & Canovi, M. (2020). Soft skills to enhance graduate employability: Comparing students and

employers' perceptions. Studies in Higher Education, 45(9), 1834–1847.

https://doi.org/10.1080/03075079.2019.1585420