Presentation

A multi-level perspective of science teaching 

and the role of video based analysis 

Hans E. Fischer 

University Duisburg-Essen 

Germany 

Hans.Fischer@uni-due.de

Outline 

1. Modeling (science) instruction 

2. The role of video based analysis 

3. Recent results of video based research 

4. Further aims 

0 1 2 3 4

Conditions for science instruction 

0 1 2 3 4 

In general: Discipline, organization of lessons, 

pacing, monitoring … 

Specific structure of subject matter 

(logic of content, scientific literacy, NOS, SI) 

Science specific teaching processes 

(experimental work, professional knowledge) 

Science specific learning processes 

(pre-knowledge, problem solving, conceptual 

development) 

System conditions 

(specific sequences, science or subjects, curricula) 

Quality of instruction

Paradigms of Quality of Instruction 

Behaviorism 

Mandl & Hron, Carroll (from 1970): Quality was operationalized as 

time on task 

Direct instruction, cognitivism 

Mayer, Rosenshine, Sweller (from 1980): information processing, 

cognitive structure, cognitive load 

Teacher personality and styles of instruction, 

subjective Theories 

Dann, Wahl, Pallasch, Shulman (from 1980): Interaction analysis, 

teacher knowledge 

Process-product-paradigm 

Helmke & Weinert (from 1990): Quality as model of instruction 

connected with students‘ performance 

0 1 2 3 4

Paradigms of Quality of Instruction 

Process-mediation-product-paradigm 

Baumert & Köller, Leutner (from 1990): processes of 

cognitive assimilation, strategies of learning and self 

regulated learning 

Offer-mediation-use-paradigm 

Klieme (from 2000): student as co-producer of his/her 

own knowledge, vertical fit of cognitive concepts, 

cognitive activation 

0 1 2 3 4

Important for quality of Instruction 

Time on task 

Information processing, cognitive structure, 

cognitive load 

Classroom interaction, teacher knowledge 

Students‘ performance 

Cognitive assimilation, strategies of learning 

and self regulated learning 

Student as co-producer of knowledge, vertical 

fit of cognitive concepts, cognitive activation


Family 

Content of the 

family 

environement 

Parents as: 

Pedagoges 

Example 

Model of 

language 

Teacher 

Instruction 

(offer) 

Quality of 

instruction 

Teachers‘ 

personality 

and expertise 

Teaching and 

learning material 

Individual pre-conditions 

Mediations- 

Processes 

Perception and 

interpretation 

of teacher and 

students 

School- and class context 

Subject and curriculum context 

Learning 

activity 

(use) 

Learning 

processes during 

instruction 

Out of school 

activities 

Effect 

(return) 

Subject specific: 

Knowkedge 

Literacy 

Abilities 

Competencies 

Others: 

Key competencies 

Socialisation 

0 1 2 3 4 

Klieme


Family 

Content of the 

family 

environement 

Parents as: 

Pedagoges 

Example 

Model of 

language 

Teacher 

Instruction 

(offer) 

Quality of 

instruction 

Teachers‘ 

personality 

and expertise 

Teaching and 

learning material 

Individual pre-conditions 

Mediations- 

Processes 

Perception and 

interpretation 

of teacher and 

students 

School- and class context 

Subject and curriculum context 

Learning 

activity 

(use) 

Learning 

processes during 

instruction 

Out of school 

activities 

Effect 

(return) 

Subject specific: 

Knowkedge 

Literacy 

Abilities 

Competencies 

Others: 

Key competencies 

Socialisation 

0 1 2 3 4 

Klieme

Research on instruction 

Teacher 

Professional 

knowledge 

Practical experience 

Background 

Instruction 

Pre-knowledge 

Motivation/Interest 

Background 

(social/ cognitiv) 

Students 

School/family 

environment 

Planning and 

performing 

Offer 

Mediation 

Use 

Experience 

Learning processes 

Practical 

experience 

Critical reflection 

Further education 

Performance 

Expectation 

Motivation/interest 

0 1 2 3 4

TIMSS, PISA 

Teacher 

Professional 

knowledge 


Background 

Instruction 

School/family 

environment 

Planning and 

performing 

Practical 

experience 



Pre-knowledge 


Background 

(social/cognitiv) 

Students 

Experience 


Performance 

Expectation 


01 2 3 4

TIMSS-Video, TIMSS-R 

Teacher 

Professional 

knowledge 


Background 

Instruction 

School/family 

environment 

Planning and 

performing 

Practical 

experience 



Pre-knowledge 


Background 


Students 

Experience 


Performance 

Expectation 


01 2 3 4

Duit, Fischer, Klieme, Labudde, IPN, 

nwu 

Teacher 

Professional 

knowledge 


Background 

Instruction 

School/family 

environment 

Planning and 

performing 

Practical 

experience 



Pre-knowledge 


Background 


Students 

Experience 


Performance 

Expectation 


01 2 3 4

Variables of instruction 

Teacher 

Cognition 

•PK 

•PCK 

•CK 

Attitudes 

• Motivation/Interest 

•Personality 

• Individual concepts 

Instruction 

Students 

Cognition 

• Knowledge, competencies 

• Learning processes 

• Behaviour 

Attitudes 

• Self-Efficacy 


• Intelligence/Aptitude 

01 2 3 4

Including Instruction 

Surface structure (Duit, Fischer, Klieme, 

Labudde, Prenzel/Seidel, Reusser …) 

Culture specific patterns, no correlation with performance 

Deep structure (Duit, Fischer, Klieme, Labudde, 

Sumfleth, Tiberghien, Viiri …) 

Rating of quality of instruction 

Level of teachers‘ offer 

Level of cognitive activation of students 

Structure of subject matter 

Communication structure, argumentation 

01 2 3 4

Cognitive activation 


Argumentation


Teacher 

Cognition 

•PK 

•PCK 

•CK 

Attitudes 




Instruction 

Teaching and learning aims, intentions of the teacher 

lesson design and teaching methods 

Teacher’s behaviour, action, media 

Teacher-student interaction 

Students’ behaviour, action, media 

Content related operations, development of meaning 

learning paths, cognitive activation 

Students 

Cognition 



• Behaviour 

Attitudes 




01 2 3 4


Teacher 

Instruction 

Students 

Cognition 

•PK 

•PCK 

•CK 

Teaching and learning aims, intentions of the teacher 

lesson design and teaching methods 

Teacher’s behaviour, action, media 

Teacher-student interaction 

Students’ behaviour, action, media 

Content related operations, development of meaning 

learning paths, cognitive activation 

Cognition 



• Behaviour 

Offer 

Attitudes 



Mediation 

Use 


Attitudes 




01 2 3 4

Methods

Surface and deep structure of instruction 

Surface Structure (low inferent coding) 

Teacher‘s behaviour, actions, media 

Students‘ behaviour, actions, media 

Teacher-student interactions 

… 

Deep Structure (high inferent coding) 

Teacher‘s aims and intentions 

Teacher‘s instructional design and methods 

Students‘ content related activities (cognitive activation) 

Students‘ learning path 

Interaction among students-teachers and students-students 

Structure of classroom talk 

… 

01 2 3 4

Developing a coding procedure 

1. Knowing the theoretical basis 

2. Developing a research question 

3. Producing data 

Video recording, Data compression, data 

segmentation, on-line or/and transcripts, … 

4. Applying the constructs of the model 

a. Determination of categories 

b. Determination of indicators 

• As clear, precise and extensive as possible 

• On the intended level of observation


5. Modeling the transfer from categories to 

indicators 

− First order coding manual containing rules, 

categories, indicators and examples 

6. Testing the coding procedure 

− 

− 

− 

− 

Estimation of reliability 

Discussing problematic coding 

Revising the coding manual 

Until the coding procedure works reliable 

(or until you have to be satisfied because of the 

timetable or lacking of money)


7. Application of the coding procedure to the 

video-recordings of interest 

8. Validity check by correlating external criteria 

if possible 

01 2 3 4

Example of a Coding Manual 

Category/Value Definition Description/Indicators Examples Dissociation 

No Instruction/ 

Interruption 

Pre-Instruction 

Instruction 

01 2 3 4 

Refers to sequences in 

which no instruction 

takes place. 

Instruction already 

took place before and 

continued later. 

All intervals are coded 

in which instruction 

does not yet take 

place. The amount of 

pre-instruction intervals 

is an indicator for 

how much time was 

actually used for 

instruction. 

All intervals are coded 

in which instruction 

takes place. The 

amount of coded 

intervals is an indicator 

for how much time was 

actually used for 

instruction (time on 

task). 

The Interruption 

usually is marked by 

non-teaching and nonlearning 

activity. 

Typically such 

Interruptions take 

longer than a coding 

interval. 

Teacher did not yet 

start with instruction. 

At the most teacher 

and students prepare 

for instruction. 

No specific description: 

Instruction takes 

place. 

Important: All 

additional coding 

refers only to intervals 

coded as instruction. 

External event or 

disruption like announcements 

or door 

knocking. Teacher 

leaves class-room, 

students remain without 

instructions. 

Clarification of formal 

or organizational 

matter. 

Students arrive at the 

classroom after the 

bell, unpack their 

books, wait for the 

teacher. 

Teacher indicating the 

beginning of instruction: 

„Lets start now“. 

Students stand up at 

the beginning of the 

lesson. 

Noise or disciplinary 

problems do not 

generally count as 

interruption; the 

action must be 

different from what 

usually happens 

during instruction. 

Separation from 

Instruction, Pre- 

Instruction is 

coded, until the 

teacher starts 

instruction. 

Mind connection 

with pre- and postinstruction. 

Instruction only 

takes place one 

time and is embraced 

by pre- and 

post-instruction 

phases. 

Georg Trendel, Rainer Wackermann, nwu-essen

Example of a Coding Manual 

Category/Value Definition Description/Indicators Examples Dissociation 

Instruction 

All intervals 

are coded in 

which 

instruction 

takes place. 

The amount of 

coded intervals 

is an indicator 

for time on 

task. 

No specific 

description: 

Instruction 

takes place. 

Important: All 

additional 

coding refers 

only to 

intervals coded 

as instruction. 

Teacher 

indicating the 

beginning of 

instruction: 

„Lets start 

now“. 

Students stand 

up at the 

beginning of 

the lesson. 

Mind 

connection 

with preand 

postinstruction. 

Instruction 

only takes 

place one 

time and is 

embraced by 

pre- and 

postinstruction 

phases. 

01 2 3 4 

Georg Trendel, Rainer Wackermann, nwu-essen

Results 

01 2 3 4

Results of Large Scale Assessments 

01 2 3 4 

Performance & culture (TIMSS/PISA): 

Competences are distributed country specific 

Strong influences from out of school (e.g. social 

background) 

Reference to Instruction (TIMSS-Video study, 

COAKTIV) 

„Scripts“ are culture specific 

Structure of lessons is dependent on conceptions of the 

teacher 

PCK and CK of the teachers are very strong variables to 

predict students‘ performance (mathematics/PISA) 

Not clarified: 

Are specific scripts responsible for specific competences ? 

How does PCK and CK influence instruction?

Expectation 

Video analysis should track the effect from 

teachers’ professional knowledge and beliefs – 

action during the lessons – students’ 

performance, knowledge and beliefs 

Video analysis as methodology to close the gap 

between teachers’ knowledge, students’ 

assessment and quality of instruction 

01 2 3 4

Descriptive Analysis (coding) 

45,00 

Surface structure: modes of interaction 

0,00 

Mean period of time per lesson [min] 

40,00 

35,00 

30,00 

25,00 

20,00 

7,25 

5,18 

2,33 0,80 

1,43 

1,52 

16,69 

2,78 

1,63 

8,84 

1,98 

2,61 

12,57 

0,14 

2,27 

5,05 

0,63 

35,63 

0,25 

3,25 

0,55 

34,55 

15,00 

28,45 29,36 

26,68 26,34 

10,00 

5,00 

0,00 

18,13 

groupwork 

seatwork 

transition 

classroom discourse 

cross section course A course B course C course D course E course F 

01 2 3 4 

Reyer & Fischer, 2004

Descriptive Analysis (coding) 

Goals of the lessons 

Learning by experience 

18,54 min 

Concept development 

13,05 min 

Diverse 

6,77 min 

Top down 

4,45 min 

Reproduction 

4,40 min 

Activation/ performance 

control 

Problem solving 

4,24 min 

3,44 min 

Routine work 

1,57 min 

Discipline 

0,79 min 

Conceptual change 

0,42 min 

No interpretation 

0,05 min 

mean per lesson [min] 

01 2 3 4 

Reyer & Fischer, 2004

Conclusions Surface Analysis 

Two types of lessons 

Student oriented teaching including experimental work 

(short and indiscriminate tasks, experiments in groups) 

Teacher centered classroom discussions, demonstrating 

experiments (mostly short answers of the students) 

Rarely students’ lectures and home work 

No correlation between surface structure and 

TIMSS-test results (TIMSS-Video, TIMSS-R, nwu) 

Correlation between surface structure and 

motivation (TIMSS-R) 

01 2 3 4

Conclusions Deep Structure 

Fact, action and apply oriented 

Factual knowledge is partly worked out by students’ 

guessing and teachers’ confirming the guessed word as 

being correct 

Action is planned in advance as step to solve a task 

(also experimental) 

Experience and concept development is applied 

incompletely 

Problem solving and conceptual change is applied very 

rarely 

01 2 3 4

Results 

Teacher level 

01 2 3 4

COAKTIV 

(Baumert, Blum, Mathematik) 

Teacher 

Professional 

knowledge 

Experience 

Background 

School background 

Lesson planning & - 

performing 

Practical 

experience 



Instruction 

Pre-knowledge 


Background 


Students 

Lesson experiences 


Performance 

Expectation 


01 2 3 4

Intervention 

Training 

(effects) 

Teacher beliefs and ideas 

(effects) 

Interaction during lessons 

(teacher and students) 

(effects) 

Rainer Wackermann 

nwu 

Students perception, 

-emotion and 

performance 

01 2 3 4

Content of the training 

Types of teaching aims (Oser) 

Learning through experience 

Conceptual change 

Problem solving 

Conceptual development 

Training 

Hypertext learning (top down) 

Motility 

Reproduction 

activation/control of learning processes and 

performance 

Discipline 

01 2 3 4

Conclusion 

Teacher training was successful on all levels 

and for all teachers and classes 

Sub-group of teachers performed even better 

than the average 

Basic models are an effective strategy for 

teaching physics 

01 2 3 4

Results 

Lesson level 

01 2 3 4

Linking of content during lessons 

Analysis of biology, chemistry and physics 

lessons 

Questions 

In which way teachers are going to link content? 

On which level students use the offered oportunities 

to learn? 

Is there a correlation between the level of teachers‘ 

offer and students‘ test results? 

01 2 3 4

Results biology 

Positive Effects of linkage regarding 

- test results 

- interest 

- willingness to make efforts 

Julia Wadouh 

Birgit Neuhaus 

Angela Sandmann 

01 2 3 4

Results chemistry 

Ina Glemnitz 

Elke Sumfleth 

Correlation between level of teachers offer and 

linking level of students‘ answers 

Correlation between linking level of students‘ 

answers and the structure of their knowledge 

More than 70% of students‘ response were on a 

low level of linkage 

01 2 3 4

Results physics 

Correlation between linking level of teachers 

offer (difficulty) and linking level of students‘ 

answers 

But: teachers tend to expect too much 

And: Students of high ranking teachers don‘t show 

better test results 

Anna Lau 

Knut Neumann 


Conclusions: The difficulty (level of linkage) 

should be better adapted to students‘ abilities 

01 2 3 4

New research question 

Anna Lau 

Knut Neumann 

Alexander Kauertz 


Elke Sumfleth 

Which variable is decisive for predicting students 

learning outcomes at school, verticale linkage or 

fit between level of teachers’ offer and level of 

students’ answer? 

01 2 3 4

Difficulty characteristics of tasks 

measuring competence in physics 

Conceptual and integrated thinking 

should lead to more complex answers 

Describing complexity by variing tasks accordingly 

Complexity as a measure to predict the difficulty of 

Structuring physics content by means of big 

ideas (basic concepts) 

Are German standards for physics able to structure physics 

content for middle school teaching? 

Is it possible to vary those structures using tasks? 

Are those tasks a measure of difficulties? 



01 2 3 4

Results 

Complexity correlates 

with diffulty 

Different basic 

concepts lead to 

different diffuculties 

The results are basis 

for a competence 

model which can 

predict students 

abilities

New research question 

Hendrik Notarp 


Knut Neumann 


Developing and validating a model for describing 

students‘ competencies in the three science 

subjects regarding content knowledge and NOS 

and SI

Perspective 

01 2 3 4

QuIP 

Quality of Instruction in Physics 

comparing Finland, Germany and Switzerland 

(Jouni Viiri, Hans E. Fischer, Peter Labudde) 

01 2 3 4


Time on task 


cognitive load 

Classroom interaction, teacher knowledge 

Students‘ performance 






Time on task, structure of the lessons 


content structure, cognitive load 

Classroom interaction, teacher knowledge and 

beliefs 

Students‘ performance and motivation/interest 





Design of the project 

Educational Background 

Family Background 

(OECD, 2002) 

Professional Knowledge 

(Schulman,1986) 

Teaching Enthusiasm 

(Kunter et al., 2005) 

Working Conditions 

Surface Structure 

Type of instruction and interaction 

Experimental groupwork ,.. (Seidel et al., 2006) 

Classroom 

Management 

Teacherbehavior 

Classroom Interaction 

(Scott & Mortimer,2005) 

Deep Structure 

CognitiveActivation 

(Lau et al., 2007; 

Trendel et al., 2007) 

Content Structure 

Bruckmann, 2007) 

Use of Experiments 

Tesch, 2007) 

Cognitive Abilities 

(Weiß, 2006) 

Competence 

(Kauertz, 2007) 

General Motivation 

(OECD, 2002) 

Situational Motivation 

(Decy & Ryan, 2000; 

Eccles, 2005) 

01 2 3 4 

Competence 


Output 

Motivation 

(OECD, 2002)

Teacher 

Instruction 

Student 



(OECD, 2002) 








Experimental groupwork ,.. (Seidel et al., 2006) 

Classroom 

Management 






(Lau et al., 2007; 





Tesch, 2007) 


(Weiß, 2006) 

Competence 



(OECD, 2002) 



Eccles, 2005) 

01 2 3 4 

Competence 


Output 

Motivation 

(OECD, 2002)

General research perspective using 

video analysis 

Developing a model of quality of instruction for 

sciences 

Describing cause-effect relations by connecting the 

different levels of science teaching 

Describing and developing didactic competences of 

teachers using video analysis and video feedback 

Connecting field studies, laboratory studies, 

experimental studies and large scale assessments 

01 2 3 4

For further information 

WWW.nwu-duisburg-essen.de

Question 

Some colleagues tell that … 

Is this true?

Research question 

How does teacher enthusiasm influence 

students‘ motivation and interest in physics? 

Is enthusiasm represented as social-supportive 

or subject-supportive behavior or else? 

Is there an influence of social-supportive or 

subject-supportive teacher behavior on 

students‘ interest and/or motivation?

What do we need to know? 

Model of enthusiasm 

Which variables are influencing enthusiasm? 

Which variables should be controlled? 

When do we know?

Tracking 



(OECD, 2002) 








Experimental groupwork (Seidel et al., 2006) 

Classroom 

Management 






(Lau et al., 2007; 





Tesch, 2007) 


(Weiß, 2006) 

Competence 



(OECD, 2002) 



Eccles, 2005) 

Competence 


Output 

Motivation 

(OECD, 2002)

Tracking 



(OECD, 2002) 



Teachers‘ Enthusiasm 





Experimental groupwork (Seidel et al., 2006) 

Classroom 

Management 






(Lau et al., 2007; 





Tesch, 2007) 


(Weiß, 2006) 

Competence 



(OECD, 2002) 



Eccles, 2005) 

Competence 


Output 

Motivation 

(OECD, 2002)

HLM 

Individual units on different aggregation levels or 

independent clusters 

There are structures of influence between hierarchic 

levels and also clusters to estimate the effect of the 

general context (culture) 

Multi level analysis allows to take into account group 

specific components of the mistakes 

The strategy leads to „correct estimated values“ of the 

mistakes regarding the sample cluster 

Variance of the regression coefficient is explained with 

characteristics of the aggregation unit

Path analysis 

More than one dependent variable 

Recursive model of variables 

Partial correlation 

Partial regression 

A B C D non recursive 

A B C D recursive

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