cognitive processes enacted by learners during...

COGNITIVE PROCESSES ENACTED BY LEARNERS DURING CO-CONSTRUCTION

OF SCIENTIFIC MODELS

Constructionism 2014 Vienna, Austria

Theodora Petrou, Christiana Th. Nicolaou1,

Pantelitsa Karnaou, Constantinos P. Constnatinou

Learning in Science Group,

Department of Educational Studies,

University of Cyprus, [email protected]

1

This work was co-funded by the European Regional Development Fund and the Republic of Cyprus

through the Research Promotion Foundation (Project DIDAKTOR/0311/92).

Contents • Theoretical framework

• The modeling competence • Research Question

• Methodology • Participants • Intervention • Modeling Tool: Dynalearn • Data Collection and Analysis

• Results • Macroscopic Analysis • Mesoscopic Analysis • Microscopic Analysis

• Discussion

2

Theoretical framework- the modeling competence

Learning by constructing models:

• denotes the process through which learners construct and use scientific models aiming at the construction of explanations about complex systems or natural phenomena (Hestenes,1987).

• learners are engaged in the processes used by scientists, who construct and use models in their everyday activities (Penner, 2000; Schwarz & White, 2005).

• learners gain understanding about how knowledge is constructed as well as about the nature of science

3

The modeling competence Constituent Components

4

Modeling practices

Meta-knowledge

construct

Compare

Evaluate and

revise

Metacognitive knowledge about the

modeling process

Meta-modeling knowledge

Use

Role of models

Nature of models

Validate

MODELING COMPETENCE

(Nicolaou & Constantinou, submitted; Papaevripidou, et al. 2007)


5

Modeling practices

Meta-knowledge

construct

Compare

Evaluate and

revise


modeling process


Use

Role of models

Nature of models

Validate

MODELING COMPETENCE


Constituent components: The modeling practices in which learners are engaged during modeling (NRC, 2012; Schwarz et al, 2009)


6

Modeling practices

Meta-knowledge

construct

Compare

Evaluate and

revise


modeling process


Use

Role of models

Nature of models

Validate

MODELING COMPETENCE


Constituent components: the meta-knowledge about the modeling competence, which includes (1) the meta-cognitive knowledge about the modeling process (Papaevripidou, Constantinou, & Zacharia, 2007), and (2) the epistemological awareness about the nature and role of models (Schwarz & White, 2005)

Theoretical framework-models

• The outcome of the modeling process is the model per ce.

• We use the concept of model as something different from mental model, and specifically, we consider that students construct scientific models, which are

• A set of systematic representations of a system or a phenomenon, which provide a mechanism about the function of the phenomenon, and allow for making predictions about the future evolution of it (Schwarz et al, 2009; Glynn & Duit, 1995).

7

Theoretical framework: COGNITIVE PROCESSES DURING MODELING

•When engaged in modeling practices, specific

cognitive processes are enacted by learners. For the present study, we adopt the framework used by Sins and his colleagues (2009), who consider that during modeling learners could be engaged in

•Analysis, • Explanation, •Quantification, • Inductive reasoning, • Evaluation

8

Theoretical framework: CONSTRUCTIONISM

• Modeling engages learners in co-constructing scientific models to gain understanding

Modeling is intrinsically related to the constructivist approach to teaching and learning

• Constructionism is based on the idea that learners construct knowledge through building artifacts, here models (Tiberghien & Malkoun, 2010; Louca & Zacharia, 2008).

9

Constructionism

Research Question

“Which cognitive processes are enacted when learners co-construct scientific

models? How is the work of two different groups compared?”

10

Methodology-Participants

• 17 students • 12 boys and 5 girls • 15-17 years old

• Summer Science Class (University of Cyprus) • 7 lessons of 90 minutes each • Learners worked in groups of 2 or 3

• Co-constructing and deploying successive models

• within their group,

• among groups in class (Face to Face) and

• through the internet (Stochasmos Learning Platform).

• Subject: simple systems in the topic of heat and temperature

11

Methodology-intervention

Modeling based learning cycle

Identify the

phenomenon Construct

model

Evaluate/validate model based on the model:

Representation/interpretation/prediction IMPROVE MODEL

Data and observations

Methodology-Modeling tool

Modeling tool: DynaLearn

(http://hcs.science.uva.nl/projects/DynaLearn/)

•Construct conceptual models, through several stages of representation (Learning Spaces)

•Construct conceptual models about simple systems which include:

• entities,

• properties of these entities,

• assign relationships (causal) to those properties

13

http://hcs.science.uva.nl/projects/DynaLearn/

Methodology-Data collection and analysis

Means of data collection:

• videotaped conversations of two groups of learners,

Software program Transana,

(for transcribing and analysing learners discussions)

Data analysis implemented the framework for analyzing videos at macro-, meso- and microscopic scale (Tiberghien & Malkoun, 2010).

14

15

Microscopic Analysis

Analysis, Explanations, Quantification, Inductive reasoning,

Evaluation Revision (Sins et al, 2009)

Mesoscopic Analysis

Macroscopic Analysis

Methodology-Data analysis

(Tiberghien & Malkoun, 2010)

• is common for all groups,

• captures task flow as it was designed by the teacher,

• no duration is noted.

16

Macroscopic Analysis


• differs for the two groups, • the conversations´ analysis is deeper, • the conversations are categorized into episodes

according to the “taught knowledge”, • duration and a title accompany each episode

(Tiberghien & Malkoun, 2010), • the theme´s title represents the theme content, • is seen as a sequence of the different episodes in

a chronological order. 17

Mesoscopic Analysis



• different analysis and outcome for different groups,

• deeper analysis of students’ conversations at this level,

• purpose: highlight the details of students’conversation,

• use of keywords to identify details

• use of cognitive processes as keywords (coding scheme of Sins, et al., 2009),

• division of each snapshot in episodes with regards to the identified cognitive process or processes,

18



19


Cognitive Processes coding scheme: • Analyse: Learners talk about/interpret modeling elements. They

identify factors that may be relevant or not to their model. They identify elements of the phenomenon that should be included in their model.

• Quantify: Learners talk about quantifying or specifying a relationship within their model. When they construct a preliminary model, they can make their ideas about model elements and relations more precise by expressing them into a mathematical form.

• Inductive reasoning: Learners elaborate upon elements within or with respect to their model (mainly qualitative reasoning). They express hypotheses on how elements interact and how they behave in their model.

20


Cognitive Processes coding scheme:

• Explain: Learners explain to each other how elements within their model work or why they were included (or excluded). Sometimes, explanation is preceded by a clear-cut question of one of the learners.

• Evaluate: Learners compare the data (the phenomenon) and their model. They determine if the model accounts for those data.


1st Ac.

•Watching videos about thermal interaction between objects with different initial temperature and equal masses.

•Conduction an experiment (temperature measurement of objects in the same environment).

•Rule 1 (The objects’ temperature, which are in the same environment is the same, if the environment is not affected by another heat source)

2st Ac.

•Processing the given experimental data (thermal interaction between objects of equal masses and different initial temperatures).

•Rule 2 (When objects with different initial temperatures touch each other, end up having the same temperature)

•Construction concept map.

•Rule 3 (When two objects with different initial temperatures touch each other, then something is transferred from the one to the other object, until the temperatures be equalized.)

3st Ac. •Construction of the basic model.

•Peer to peer Assessment.

21

Results- Macroscopic Analysis

5th Ac.

•Watching videos about thermal interaction between objects with different initial temperatures and masses.

•Discussion about the videos.

6th Ac.

•Processing the given data (thermal interaction between objects with different initial temperatures and masses).

•Rule 4 (When objects with different initial temperatures and masses touch each other, then heat is transferred from the one to the other until the temperatures be equalized).

7th Ac.

•Improvement of the basic model – Constructing the second model (advanced version of first model).

•Peer to peer assessment.

•Rule 5 (Heat is transferred from the object with higher temperature to the object with lower temperature. The temperature of object with lower mass is changing more than the temperature of heavier object. The ratio of masses is inversely proportional to ratio of the temperature changing.)

4th Ac.

•Presentation in the whole class for specific aspects of the nature of scientific models and modeling.

22

Date 01/07/2013 - Lesson 1: Group 1

Episode and Title Description Duration 1. Instructions by the

instructor

The instructor introduces the content and the process of the course

to the students. Students watch a video about thermal interaction

of bodies

0:12:48

2. Task 1, Temperature

measurement

Students measure the temperature of objects in the class

environment

0:22:01

3. Task 1. Rule1: same

environment same

temperature

Express rule 1: objects in the same environment have the same

temperature, if no heat sources are present

0:20:52

4. Task 2, Data set 1:

“Contact of bodies with

different temperature and

the same mass”

Students elaborate on the given data of the first experiment (two

objects of the same mass and different temperatures contact each

other) and try to identify patterns out of them

0:01:52

5. Task 2, Rule 2 Students report their conclusions with regards to the data of the

first experiment. They write down the second rule: when two

objects interact thermally they reach the same temperature.

0:00:33

6. Task 2, concept map

“thermal interactions of

bodies”

Students build a concept map in the modeling tool (DynaLearn)

about the ideas emerged by the two experiments and which

concern the thermal interactions of bodies.

0:03:40

Example

24

Results- Mesoscopic Analysis

Date 01/07/2013 - Lesson 1: Group 1

Episode and Title Description Duration 1. Instructions by the

instructor

The instructor introduces the content and the process of the course

to the students. Students watch a video about thermal interaction

of bodies

0:12:48

2. Task 1, Temperature

measurement

Students measure the temperature of objects in the class

environment

0:22:01

3. Task 1. Rule1: same

environment same

temperature

Express rule 1: objects in the same environment have the same

temperature, if no heat sources are present

0:20:52

4. Task 2, Data set 1:

“Contact of bodies with

different temperature and

the same mass”

Students elaborate on the given data of the first experiment (two

objects of the same mass and different temperatures contact each

other) and try to identify patterns out of them

0:01:52

5. Task 2, Rule 2 Students report their conclusions with regards to the data of the

first experiment. They write down the second rule: when two

objects interact thermally they reach the same temperature.

0:00:33

6. Task 2, concept map

“thermal interactions of

bodies”

Students build a concept map in the modeling tool (DynaLearn)

about the ideas emerged by the two experiments and which

concern the thermal interactions of bodies.

0:03:40

Example

25

Results- Mesoscopic Analysis

3. Task 1. Rule1:

same

environment

same

temperature

Express rule 1: objects in the same

environment have the same temperature,

if no heat sources are present

0:20:52

• The cognitive processes in which learners were engaged during modeling (total work time=630 minutes).

Group 1 Group 2

Cognitive Processes Duration Cognitive Processes Duration

Inductive Reasoning 1:03:43.7 Inductive Reasoning 0:41:42.0

Explain 0:58:00.9 Evaluate 0:27:07.0

Evaluate 0:33:23.5 Explain 0:12:00.0

Analyse 0:18:40.4 Analyse 0:09:21.0

Quantify 0:14:46.2 Quantify 0:08:03.0 26

Results- Microscopic Analysis

• The cognitive processes in which learners were engaged during modeling (total work time=630 minutes).

Group 1 Group 2

Cognitive Processes Duration Cognitive Processes Duration

Inductive Reasoning 1:03:43.7 Inductive Reasoning 0:41:42.0

Explain 0:58:00.9 Evaluate 0:27:07.0

Evaluate 0:33:23.5 Explain 0:12:00.0

Analyse 0:18:40.4 Analyse 0:09:21.0

Quantify 0:14:46.2 Quantify 0:08:03.0 27



• Both groups spent most of their time in Inductive Reasoning and least of their time in Quantification

• Students are engaged in the specific cognitive processes in quite a similar order.

• Explaining was most common for group 1 and less common for group 2 when comparing with the cognitive process of evaluating.

28

Discussion • The teaching sequence was common for both groups

(Macroscopic scale)

• The sequence and the variety of the discussions and the work of the two groups held many commonalities, but, specific differences were also identified. (Mesoscopic scale)

• Students of both groups were engaged more in inductive reasoning and less in quantification (Microscopic scale)

• Students of group 2 were engaged in the same cognitive processes as group 1 but for a longer period (Microscopic scale)

29

Discussion

• The reason behind this difference:

• Students of group 1 were talking out all the concerns, problems, arguments or counterarguments at the intragroup level of collaboration (within group), which resulted in a process of collectively solving problems and collaborating to reach the group’s goals.

• Students of group 2 tended to work silently without externalizing their thoughts much. They were working most of the time on the computer and while collaborating, sometimes even through gestures they were not externalizing those conversations

30

Discussion Findings from the microscopic analysis:

• Students of both groups spend their time mostly for identifying or discussing qualitative relationships between model’s elements and the least of their time on quantitative relationships.

• This finding contradicts the results of other research (Sins et al, 2009), which indicated that quantification was the most common cognitive process enacted by students when using Powersim as a modeling tool.

31

Discussion

• The inconsistency seems to be explained by the different software used in the two studies.

• DynaLearn supports the construction of qualitative relations, therefore it prompts learners to discuss and think of the qualitative relations of model elements.

• Powersim, on the other hand, supports the construction of quantitative relations and pushes learners to think and act quantitatively.

32

Discussion

• The modeling tool used by learners as a means to construct their models guides their cognitive efforts and could lead to different learning pathways (Louca & Zacharia, 2008).

33

COGNITIVE PROCESSES ENACTED BY LEARNERS DURING CO-CONSTRUCTION

OF SCIENTIFIC MODELS

Constructionism 2014 Vienna, Austria

Theodora Petrou, Christiana Th. Nicolaou1,

Pantelitsa Karnaou, Constantinos P. Constnatinou

[email protected] 34

Thank you for your attention

cognitive processes enacted by learners during...

Documents