PfDK – Visualization Editor

Fig. 1

Digital assignments by subject

135

total assignments

27%

are digital (n=37)

23

total exam

9%

are digital (n=2)

Bars show % of each subject's assignments that are digital (n digital / n total). Sorted descending. Subjects with 0 digital are included at the bottom. The stat boxes at top show programme-wide totals.

Fig. 2

Digital assignments per semester

Two axes: The line (left axis, %) shows what fraction of that semester's assignments were digital. The bars (right axis, count) show the raw total number of assignments — bar height is on a different scale than the line. A tall bar with a low line = heavy semester with few digital tasks; short bar with high line = light semester that was mostly digital.

Fig. 3

Integration level (TPACK score)

TPACK score (3–9) measures the quality of technology integration across Technology, Pedagogy, and Knowledge dimensions. Grouped into three levels: Low (3–5), Moderate (6–7), High (8–9). Only the 37 digital assignments are scored.

Fig. 4

TIM level – digital assignments

TIM level classifies how technology is integrated: Entry = basic tool use with no change to instruction; Adoption = using tools as a direct substitute; Adaptation = technology modifies the task; Infusion = technology integrated throughout; Transformation = technology enables entirely new, subject-transforming activities. Each digital assignment is coded at one level.

Fig. 5

Cross-table: TPACK level × TIM level

Frequency:

0

1

2–3

4–5

6+

Cross-table of TPACK quality (rows) × TIM integration level (columns). Cell values = number of digital assignments. Darker cells = higher frequency. Most assignments cluster in Low-moderate TPACK × Adoption/Adaptation TIM — suggesting a middle-of-the-road quality ceiling across the programme.

Fig. 6

Subject profile: Volume and quality (bubble chart)

Crosshair lines: Dashed vertical = mean digital assignments across subjects; dashed horizontal = mean TPACK score. Four quadrants: top-right = high volume + high quality; bottom-right = high volume but low quality (Social Science). Bubble size = % of subject's total assignments that are digital.

Fig. 7

TIM distribution by subject (stacked bar)

Stacked bars show the absolute count of digital assignments per TIM level for each subject. Same data and subject order as Fig. 6 (sorted by total digital assignments, descending). Compare bar compositions across subjects: Language has many at Entry and Adoption; Music and Maths reach higher levels (Transformation). To edit subject data, use the editor in Fig. 6.

Fig. 8 – Table

All subjects – digital assignments and integration quality

Subject	Tot.	Dig. (% of all)	%	TPACK (mean)	TIM distribution

Table ordered by number of digital assignments (descending). Tot. = all coded assignments in the subject; Dig. (% of all) = digital assignments (and their percentage share of the total 37 digital assignments across the entire curriculum); % = share digital within the subject; TPACK (mean) = average score across digital assignments (scale 3–9). TIM pills show how that subject's digital assignments are distributed across integration levels.

Fig. 9 – New

TIM level by subject – assignment count as bubble size

Subjects sorted with most digital assignments at top (same order as Fig. 8). Bubble area is proportional to n; number inside = exact count. Zero-count cells are empty. Compare columns to see which TIM levels are used across subjects — and which subjects drive each level.

Fig. 10 – Theoretical model

Ideal PfDK integration: TIM progression across semesters

All subjects participating equally · TPACK ≥ 8.0 throughout · Consistent progression from basic to advanced integration

How to read this figure: x-axis = semester (1–9), y-axis = TIM level (Entry at bottom, Transformation at top). Bubble size is proportional to the hypothetical number of assignments at that level in that semester. The amber dashed arrow traces the weighted centroid — where the "centre of gravity" of integration quality ideally lies each semester. A steeply rising centroid means rapid progression toward transformative use. Compare directly to Fig. 12 (empirical) to assess where actual practice diverges from this ideal.

Fig. 12 – Empirical

Actual TIM progression across semesters

Same structure as Fig. 10 (theoretical ideal) — compare to see where real progression diverges from the ideal

How to read this figure: x-axis = semester (1–9), y-axis = TIM level (Entry at bottom, Transformation at top). Bubble size is proportional to the actual number of assignments at that level in that semester. The slate dashed arrow traces the weighted centroid — showing how the "centre of gravity" of real TIM integration shifts across the programme. A flat or descending centroid indicates that more advanced integration is not being reached in later semesters. Compare directly to Fig. 10 (theoretical ideal) to identify gaps.

Fig. 11

TPACK component profile by subject

Mirror of Fig. 1 — subjects with the highest % digital assignments may reveal uneven Technology / Pedagogy / Knowledge integration

Each radar shows a subject's estimated Technology / Pedagogy / Knowledge balance (scale 0–9). Subjects are ordered by % digital assignments, matching Fig. 1. A high Technology score alongside lower Pedagogy may indicate that technology use is not yet deeply integrated pedagogically. The small bar below each radar mirrors Fig. 1 — bar width = % digital. These are estimated component scores; update them via the editor.

Fig. 17

TPACK Assignment Profile: Language vs. Social Science

Individual assignment scores (scale 1–3) for Technology, Pedagogy, and Content

Language assignments (n=15)

Social Science assignments (n=5)

Radar charts showing Technology (T), Pedagogy (P), and Content/Knowledge (C) scores for individual assignments in Language (left) and Social Science (right). Coded on a 1-3 scale (summing to the total TPACK score of 3-9). Concentric grid lines represent scores of 1, 2, and 3.

Fig. 13

Activity type: Consume · Produce · Reflect

Left: volume per semester · Right: count per subject

By semester — n per type

By subject — n per type

Activity types: Consume = receptive/passive use of digital tools (e.g. watch, read, listen); Produce = creative/active creation with digital tools (e.g. record, design, write); Reflect = metacognitive or evaluative use (e.g. assess, portfolio, peer review). Left panel shows how the mix shifts across semesters; right panel shows each subject's overall balance. Compare to Fig. 14 (theoretical ideal) and Fig. 15 (empirical bubble matrix).

Fig. 14 – Theoretical model

Ideal activity-type progression across semesters

Consume → Produce → Reflect · Progression from receptive to metacognitive digital use

How to read this figure: Each bar = one semester, stacked to 100% of that semester's digital assignments. The amber dashed line is the progression index — a weighted score from 0% (all Consume) to 100% (all Reflect), computed as (Produce% + 2·Reflect%) / 2. The ideal shows a clear upward trend: early semesters are Consume-heavy; later semesters shift toward Produce and Reflect. Compare the line's slope to Fig. 15 (empirical) to see whether actual practice follows this progression.

Fig. 15 – Empirical

Actual activity-type distribution across semesters

Same structure as Fig. 14 (theoretical ideal) — compare to see where actual activity type use diverges

How to read this figure: Each bar = one semester, stacked to 100% of that semester's digital assignments (semesters with 0 digital assignments are empty). The slate dashed line is the progression index — 0% = all Consume, 100% = all Reflect, computed as (Produce% + 2·Reflect%) / 2. A flat or irregular line indicates that higher-order activity types are not being systematically developed across the programme. Compare directly to Fig. 14 (theoretical ideal) to identify where empirical practice falls short.

Fig. 16 – Table

Semester portfolio breakdown

Sem	ECTS	Subject	Type	Tot.	Dig.	% Dig.	Share Digital	TPACK (mean)	TIM (mean)

Semester-by-semester view of the entire study portfolio. Shows ECTS credits, course type (Compulsory vs Elective), total assignments, and digital assignments with percentage shares. Only some subjects in a semester are elective, and students choose one 30-ECTS elective path.

Fig. 18 – Special Analysis

The PfDK Pathway Lottery and Master's Drop-off

Analytical cross-examination of student elective choices and curriculum digital exposure over 5 years

Elective Pathway Exposure & Quality Variance

Elective Pathway Selection (Sem 1 & 3)	Tot. Dig. Tasks	Avg. TPACK Score

Key Insight: A student's digital competence exposure is subject to a "lottery". Choosing the Arts & Crafts + Religion path results in just 22 digital tasks. Conversely, choosing Social Science + Professional Pedagogy yields 30 tasks, but at a significantly lower integration quality (TPACK 5.30 vs 5.88 in the Science path).

Semester Exposure Decay (Masters Drop-off)

Progression Failure: Instead of building up progressive digital capabilities, coursework digital tasks decay significantly over time, reaching exactly 0 digital assignments in Semester 8, and just 1 in Semester 9.

Analysis based on the combined study curriculum portfolio dataset. Shows how individual elective choices create significant gaps in both cumulative volume and average quality of technology integration, compounded by a sharp progression drop-off in the final Master's level semesters.

Fig. 19 – Special Analysis

Reflection Type: Documentation Medium vs. Pedagogical Object

Analysis of coursework reflection assignments against the Norwegian PfDK Framework (Kelentrić et al., 2017)

Coursework Reflection Tasks (n=4)

Assignment	Subject & Sem	Reflection Role / Classification	TPACK	TIM

Key Insight: True PfDK reflection requires critical thinking on digital tools and their pedagogical implications. In the curriculum, only one task (A110, Language Sem 6) does this. The other 3 tasks merely use technology as a documentation medium to record teaching practice, meaning students reflect on the practice itself rather than the technology.

Role of Digital Technology in Reflection

25% Reflection ON Technology (PfDK Object)
75% Reflection WITH Technology (Documentation Medium)

Qualitative classification of the 4 coursework reflection assignments. Direct PfDK reflection (Technology as pedagogical object) is critical for professional digital competence, but remains underrepresented compared to standard reflective practice using video capture.

Fig. 20 – Special Analysis

Cumulative Coursework Workload vs. Digital Competence Exposure

Cumulative progression of total coursework requirements versus digital coursework requirements across semesters 1–9

Figure 20: Cumulative progression of total coursework tasks vs. digital tasks across the 5-year study program. The dashed line represents the total workload (cumulative assignments, both digital and non-digital) for the pathway with the maximum number of tasks (Social Science + Professional Pedagogy). The solid colored lines track the cumulative digital assignments for the three distinct student pathways: Max. Quantity (Social Science + Professional Pedagogy, 30 tasks), High Quality (Science + Physical Education, 25 tasks), and Min. Exposure (Arts & Crafts + Religion, 22 tasks). The large gap between the total workload and the digital lines highlights that digital assignments constitute only a minor fraction (24%–32%) of the total coursework, while the plateau in Semester 8 represents the Master's level drop-off.