Thinking Outside the Animation-Box
A Quasi-Experiment to Explore the Impact of Instruction Methods on Children’s
Knowledge Gain, Creativity, and Enjoyment in a Museum
J.S. IJpma (Yessica) Student number 10352775 January 29th 2015
Master thesis Communication Science
Youth & Media
Abstract
Research on instruction is most-often limited to schools. The present research aimed to explore the effects of different kinds of instruction on children’s museum experience. The focus was set on the impact of explicit real life instruction, implicit real life instruction, and computer-mediated instruction, and their effect on children’s substantive cognitive
development, creativity, and enjoyment. This research question was tested in a quasi-restricted area of a museum, using a specific exhibition item, and a clear assignment. In December 2014, 92 children (aged 4-15) participated in present quasi-experimental study. Results showed that, although the results were not far from significant, different instruction methods did not lead to substantively more knowledge. Explicit instruction showed most beneficial effects for cognitive development and creative stimulation of children, compared to the effects of the implicit instruction and the computer-mediated condition. Next, real life instruction led to more pro-activity, interactivity, and explicit need of guidance than computer-mediated instruction. Computer-mediated instruction was experienced as most difficult. More research on instruction in museum settings is needed in order to provide
museum professionals recommendations on the use of varying instruction methods in museum designs.
Thinking Outside the Animation-Box
A Quasi-Experiment to Explore the Impact of Instruction Methods on Children’s Knowledge Gain, Creativity, and Enjoyment in a Museum
Instruction is most-often studied in terms of teaching methods in formal education: schools. Results showed that learners’ cognitive- and creativity development, and emotional appeals can be influenced by teaching methods in different ways (Vermunt & Verloop, 1999). When it comes to the degree of control, previous research showed that high teacher-control elicits more passive learners’ behavior, whereas looser teaching strategies trigger more proactive learners’ behavior (Vermunt & Verloop, 1999). More recent research studied teaching methods in terms of explicit and implicit instruction. Results show that – in line with early research on high degrees of teacher control, children demonstrate substantively more substantive cognitive progress when the effects are compared to looser teachers’ behavior (Vermunt & Verloop, 1999; Loveless, 2002). On the other hand, when it comes to the
development of more complex cognitive skills (e.g. divergent thinking, problem-solving, and creativity), looser instruction methods would be more preferable (Beek, 2011; Strom & Strom, 2011). As results pointed out, (pro)active learners’ behavior is triggered by this
method. Consequentially, implicit instruction proved to lead to a higher degree of experienced self-control, engagement, and feelings of empowerment (Vermunt & Verloop, 1999; Beek, 2011; Strom & Strom, 2011). Moreover, implicit teaching methods also benefit socio emotional aspects, e.g. raised levels of intrinsic motivation, satisfaction, and enjoyment (Jeffrey & Craft, 2011; Strom & Strom, 2011; Beek, 2011).
However, substantive knowledge development was - and still is most-often, the main pillar of formal education. Therefore, it is important to notice that – recently, debates on educational norms and values are raised. Researchers, politicians, educative professionals and
caregivers question the traditionally set norms of education. Are math, language, science, and physics still the most important focus points of education or do children also need to develop other skills and competences in order to keep up with future society’s needs? This resulted in research on so-called 21st Century Skills; a list of important skills for 21st century needs
(Voogt & Pareja Roblin, 2010). Moreover, these discussions also led to a national Dutch debate: the government started a national forum in order to discuss relevant focus points for future-oriented education (Rijksoverheid, 2014).
Previous research shows that many researchers argued that future society’s education looks completely different. Not only do children need to develop other skills and competences - formal learning and informal learning will overlap more and more. The information
technology created possibilities for learners to make many choices regarding taking lessons at school, study at home, and/or use school-settings solely for interactive guidance and
cooperation. These developments led to field research on i.a. ‘e-learning’, ‘flipped
classrooms’, ‘personalized education’, and ‘gamified learning’ (Okan, 2003; Kratwohl, 2002; Voogt & Pareja Roblin, 2010). Schools seem to experiment more and more with these new educative designs, and results are promising (Kong e.a., 2014). Moreover, school time schedules became more flexible, and ICT innovations created – and promise to create, many more possibilities to meet learners’ personal needs and preferences. Results showed that computer-mediated learning can enhance cognitive, emotional, linguistic, and literacy skills due to its flexible capacities – even when it comes to preschool learners (Vernadakis, Avgerinos, Tsitskari, & Zachopoulou, 2005)
However, it also seems to be broadly acknowledged that computers cannot ever replace the interactivity and appeals of real-life communication (Vernadakis e.a., 2005; Missildine, Fountain, Summers, & Gosselin, 2013). Results seem sometimes contradicting; although computers show promising results when it comes to personalizing education, fitting
individuals’ needs, developmental levels and preferences, guiding learning processes.
However, human support seems indispensable (Vernadakis e.a., 2005; Loveless, 2002; Jones & Issroff, 2005).
When it comes to other informal learning environments than school-external settings - where children work on their formal school assignments, researchers often bring up museums as educative stimulating areas (Bamberger & Tal, 2006; Ballofet, Courvoisier, & Lagier, 2014). As argued, museums represent stimulating educative environments where aesthetics, entertainment, and appeals are very important, time frames are almost absent, and rules are limited to a minimum compared to formal education. This makes museum environments theoretically ideal to stimulate children’s knowledge development, complex cognitive skills, and enjoyment (Bamberger & Tal, 2006; Strom & Strom, 2011).
As shown, research on instruction, learning and enjoyment in museums - other than science museums, is limited. Research on the impact of teaching and instruction is most-often limited to schools. Present paper will try to contribute to filling this gap. A quasi-experiment will be used to answer the following main research question:
What is the impact of variation in instruction strategies on substantive knowledge, creativity, and appeals of children in a museum?
Theory Instruction Methods
Most research on instruction has been done in terms of teaching styles, and consequently – was often performed in formal learning settings: schools (e.g. Vermunt & Verloop, 1999; Coffield, Moseley, Hall, & Ecclestone, 2004). Research on instruction, showed that teaching styles and learning styles should be matched in order to create most ideal learning circumstances (Vermunt & Verloop, 1999). According to Vermunt & Verloop (1999), teaching styles can be varied most roughly in terms of teacher-control. They showed that learners have different preferences concerning the amount of guidance they need - and wish from their teacher (Vermunt & Verloop, 1999). In more recent research, this topic of interest is often discussed in terms of ‘explicit versus implicit instruction methods’ (Beek, 2011; Witt, Puspitawati, & Vinter, 2013).
Explicit instruction. Explicit instruction is in most research characterized as: linear,
hierarchic but learner-oriented, clear intentional whereby clear explanations are given, rules provided and goals are set (Beek e.a., 2011; Kemper, Verhoeven, & Bosman, 2012; Witt, Puspitawati, & Vinter, 2013). Results of research on explicit teaching strategies showed that learners tend to take a more passive and receptive role compared to instruction settings where teachers used looser teaching methods (Vermunt & Verloop, 1999). On the other hand, explicit instruction has benefits for educative objectives, especially for normative education goals. As Damhuis, Segers and Verhoeven (2014) pointed out, explicit instruction prompts broader -, and more in-depth knowledge than implicit instruction, even when it comes to pre-schoolers. Explicit instruction is widely acknowledged as an effective teaching strategy (Verloop & Vermunt, 1999; Khifhfe & Abd-El-Khalick, 2002; Beek, 2011). Learners
demonstrate evidently more progress and substantive knowledge gain when explicit methods are used compared to implicit instructions (Beek, 2011). However, as Beek (2011) also
showed, explicit instruction can possibly lead to higher degrees of experienced pressure, which negatively impacts learners’ self-esteem, emotional appeals, and eventually: their achievements.
Implicit instruction. Implicit teaching is most-often characterized as: a loose teaching
technique, non-linear, free of a clear structure, without elaborate explanations or clearly demonstrated rules with a strong focus on encouraging students to learn discovery-based, and a lack of strict guidance (Kemper, Verhoeven, & Bosman, 2012; Witt, Puspitawati, & Vinter, 2013). By the use of implicit instruction, learners are stimulated to be proactive and take control over their own learning processes (Damhuis, Segers, & Verhoeven, 2014). Implicit instruction often goes hand-in-hand with analogy learning, which is teaching based on examples (Beek, 2011). Results show that implicit teaching methods trigger learners to
become more engaged compared to effects of explicit instruction. This is due to the belief that implicit instruction triggers feelings of ownership, and control, resulting in triggered intrinsic motivation, raised levels of enjoyment, higher levels of self-esteem, and eventually: more feelings of appeal than explicit instruction (Donald, 1991; Strom & Strom, 2011; Beek, 2011; Damhuis, Segers, & Verhoeven, 2014).
Additionally – although previous research showed that learners show less substantive cognitive development due to the use of implicit teaching strategies compared to explicit methods, other authors demonstrated on the contrary that more complex cognitive skills - e.g. problem-solving, divergent thinking and creativity, are more stimulated through implicit instruction than through explicit instruction (Loveless, 2002; Strom & Strom, 2011). This would be due to the stimulating value of implicit instruction for explorative-, discovery oriented learning (Loveless, 2002; Strom & Strom, 2011).
21st Century Learning
Currently, more complex cognitive skills are popular focus points of researchers, educative professionals, politicians and caregivers. In December 2014, the government (re)opened a debate on whether traditional norms and goals of education are still up-to-date for future society (Dekker, 2014; Rijksoverheid, 2014). Previous research discussed future oriented skills in terms of so-called 21st Century Skills (Voogt & Pareja Roblin, 2010). It is broadly acknowledged by many researchers and politicians that times change. Children might need other skills and competences in order to grow and have success in future’s increasingly digital, connected society (Voogt & Pareja Roblin, 2010; Strom & Strom, 2011). Among those 21st Century Skills - next to e.g. ICT literacy, Creativity is one of the most common focus points (Kratwohl, 2002; Voogt & Pareja Roblin, 2010; Strom & Strom, 2011).
Surprisingly, even in Bloom’s revised learning model, Kratwohl (2002) placed Creativity at the end of the learning process: the ultimate goal of education. However, the competence is characterized by many different dimensions, researchers argue that creativity can be affected by many factors, and overall it seems a complex cognitive competence (Kratwohl, 2002; Voogt & Pareja Roblin, 2010; Strom & Strom, 2011). Therefore, Creativity will be studied as specific dependent cognitive variable.
Due to results of previous research, the following hypotheses were proposed:
(H1) The explicit instruction will yield more substantive knowledge than the implicit instruction;
(H2) The implicit instruction will appeal children more than the explicit instruction;
(H3) The implicit instruction will stimulate the creativity of the children more than the explicit instruction.
Individual Instruction Style Preferences
It is widely acknowledged that every individual has its own educative preferences and – in order to create most perfect learning circumstances for ever individual, teaching styles should ideally be matched with learning styles. (Vermunt & Verloop, 1999; Coffield, Moseley, Hall, & Ecclestone, 2004). However, it is also widely acknowledged that it is difficult to meet every individual’s preferences and needs in school settings, with only one available real life teacher and many more students, all with their own personalities (Vermunt & Verloop, 1999). Therefore, personalized, ideal educative settings seem difficult to achieve in school settings. Computer-mediated tools – with their pace, flexibility and broad array of possibilities, offer promising possibilities in order to meet individual learner’s needs due to the fact that learners can use computers independently. Computers can easily test individuals’ developmental levels on a broad variety of subjects, and consequently meet their needs and preferences (Kong, Chan, & Griffin e.a., 2014). Could computers be the ideal future educative guides?
Computer-Based Learning
Computer-based learning is a broad subject in the field of research. Due to a broad range of possibilities to involvement computers in educative settings, many ways of
computer-use are possible. This can vary e.g. in terms of computer-assisted teaching at school to e-learning at home. As a result, researchers studied topics as ‘e-learning’, ‘flipped
classrooms’, and ‘blended learning environments’ (Missildine e.a., 2013; Kong e.a., 2014). These computer-mediated education designs made it possible to make learning more flexible, dynamic, content fitting to personal developmental degrees and preferences, and bring formal and informal learning settings closer to each other. ‘Flipped classrooms’ for example,
represent home-based education, whereas time at school is used for teacher-guidance and Q&A-sessions (Missildine e.a., 2013). Results show promising benefits to meet personal
needs and preferences, although not every researcher agrees that computer-based learning is the most stimulating way of learning.
In order to guide learners’ in a specific direction, guiding instruction is still often needed (Vernadakis e.a., 2005). Instruction can be varied in terms of real life teacher-control (Vermunt & Verloop, 1999). However, computer-based tools can instruct learners’ too. Research showed that computer-mediated teaching can have many benefits for learners, even when it comes to pre-schoolers (Vernadakis e.a., 2005). Results showed that the most
significant advantages of computer-use are: (1) The potential to individualize instruction; and (2) The possibility to present material in various ways (e.g. by using text, audio, graphics, combinations etc.). Latter argument has many benefits, whereas learners’ preferences are not limited to the aspect of teacher-control and – guidance. Some children prefer to learn visually, auditive, or interactively (Coffield e.a., 2004; Kolb & Kolb, 2005). Computers created more possibilities to meet those preferences than ever before. They prove to be possible ideal tools for learners’ self-expression, creativity, and collaborative learning. The educative speed and level can easily be varied and adapted, and computers have many possibilities for interactive learning (Loveless, 2002, Jones & Issroff, 2005). As a result, research shows that computer-mediated learning shows big promises for optimal cognitive - and social emotional
stimulation of children. ICT tools proved to be very useful for special education too. Especially to capture the attention of children with attention difficulties (Vernadakis e.a., 2002).
Moreover, research shows that children enjoy playing and working with computers very much. This is due to the high level of own impact on - and control over processes which leads to feelings of empowerment, engagement, and raised levels of self-esteem (Loveless, 2002; Kong e.a., 2014). Next, the broad array of possibilities to adapt content to preferences and add game-features (so-called gamification) makes an important contribution to feelings of
entertain- and enjoyment (Loveless, 2002; Okan, 2003; Vernadakis e.a., 2005; Jones & Issroff, 2005).
For those reasons, the following hypotheses were proposed:
H4) The computer-mediated instruction will stimulate the substantive cognitive development of the children more than the real life instruction;
H5) The computer-mediated instruction will stimulate the creativity of the children more than the real life instructions;
(H6) The computer-mediated instruction will appeal more to children than the real life instructions.
Formal and Informal Learning
Recently, researchers stressed the fading boundaries between formal and informal learning environments (Kong e.a., 2014). Computes made an important contribution to these blurred boundaries (Loveless, 2002; Kong e.a., 2014). As shown in previous sections, these innovations contributed to increased experiments with school external learning settings. However, so-called ‘informal learning’ is not bound to formal educative content nor to specific environments. The objective of informal learning can also be found in games (which can be played at home), didactic television shows; and also in museums. It is widely
acknowledged that museums are very suitable for children’s cognitive and socio-emotional stimulation (Packer & Ballantyne, 2002; Bamberger & Tal, 2006; Anderson, Piscitelli, Weier, Everett, & Tayler, 2002).
Museum-based learning. Most research in the field of museum-based learning
focused on science oriented museums. Next to that, the focus points were often: the overall design, specific exhibitions or the design of exhibition items (Anderson e.a., 2002; Bamberger & Tal, 2006). However, museum researchers argued quite frequently that museum are ideal environments to stimulate imagination, discovery-based learning and children’s creativity
(Donald, 1991; Bamberger & Tal, 2006; Anderson e.a., 2002). According to Anderson e.a. (2002) this is due to the fact that – opposed to formal education environments, children tend to connect museum experiences more easily with personal (home-based) cognitive
experiences. Next, the common use of entertaining narratives, guidance by educative museum professionals, and museums’ overall strong focus on aesthetic and entertaining presentation of information make an important contribution to the stimulation of cognitive and social
emotional development of children (Anderson e.a., 2002).
However, museums struggle often with balancing educative deepness with ‘fun-aspects’, without risking the brand mark of an amusement park (so-called ‘Disneyfication’; Ballofet, Courvoisier, & Lagier, 2014). This could be threatening for the educative value. On the other hand, researchers have also shown that entertainment and education are not always competitive. They can be synergistic as well. This means that their combination can produce greater effectiveness than their individual effects (Packer & Ballantyne, 2004). Summarizing, instruction in combination with educative entertainment (in museums) still seems to be a complex experience (Anderson e.a., 2002; Ballofet, Courvoisier, & Lagier, 2014). Therefore the present research tried to contribute to more knowledge on this topic of interest.
Based on the theory, the following model was proposed:
Figure 1: Research Model
Explicit real life instruction Substantial knowledge
Implicit real life instruction Creativity
Computer-mediated instruction Enjoyment H2 H3 H5 H1 H4 H6
Method Participants
On three days in December 2014, 92 children participated in the present research. The participants were selected through stratified sampling in order to create a balanced sample for this quasi-experimental design. The participants and their guides or parents happened to visit the museum by chance on one of the experimental days. Children were asked to participate with one or two other kids in order to exclude social support bias (So & Brush, 2008). Ages ranged between 4 and 15 years old (M = 8.87, SD = 2.70). Five participants were excluded from the sample due to age-outliers (18, 19 and 36), or because of their wish to participate solely on their own (two children). Consequentially, analyses were performed on 87 participants (N = 87, 47% Male).
The children were tested on three different days, with one experimental condition tested on each day different day. On December 13, the computer-mediated instruction condition was tested (N = 26, 57.7% Male, Mage = 8.46, SDage = 2.78), on December 20 the
implicit instruction condition (N = 31, 32.3% Male, Mage = 8.77, SD age = 2.38), and on
December 21st, the explicit instruction condition was tested (N = 30, 53.3% Male, M age =
9.33, SD age = 2.94). In order to test whether the samples of the different conditions did not differ significantly, a one-way ANOVA was performed. Results of this test showed that there were no significant differences in age nor gender between participants in the different
experimental conditions.
Procedure
Location. The location chosen for the study was The Netherlands Institute for Sound
and Vision (Beeld & Geluid (B&G)). B&G is a specific kind of museum: it is one of the largest audiovisual archives in The Netherlands. The museum manages 70% of all Dutch audiovisual heritage, which is used for the exhibition of B&G. (Beeld & Geluid, 2014). In
order to examine the impact of instruction, a specific exhibition item was chosen for the research. This made it possible that the research could take place in a quasi-restricted area of the museum, and create a setting with results as valid and reliable as possible. The specific exhibition item which was chosen for the research was a stop-motion animation machine. This machine was specifically designed for- and property of B&G.
The stop-motion animation machine. The stop-motion animation machine was
designed to make stop-motion animation movies easily, without much pre-knowledge. The machine is built into a (kids-high) cabinet on wheels, with a large worksheet on top to put material on for the animation-films. Two cameras focus on this worksheet, a computer screen is connected, and the computer is built into the cabinet in order to watch the produced
animations instantly. Furthermore, the stop-motion animation facilities can be controlled by two big buttons: a big red button takes pictures and a black button deletes pictures. The computer screen can be controlled with a keyboard and a touchpad. For the present research, craft material such as paper, scissors, pencils, and ready-made material, e.g. plastic dinosaurs, stars, fish and fluffy glitter balls were provided for the content of the animation-movies for this assignment.
Moreover, the stop-motion machine was installed on the main floor of the exhibition, as general (but quasi-restricted) part of B&G’s exhibition. A sign announcing
“Stop-animation workshop: Do you want to design stop-motion “Stop-animations?!” was placed in front of the exhibit item and the stop-motion machine was guided by a B&G attendant and the
researcher. The researcher took a passive role, while the accompanying B&G attendant actively approached B&G-visitors in order to recruit participants for the research.
Procedural design. In every condition, the procedure started with the active
recruitment of participants through the B&G-attendant. Before the experiment started, the children’s parents or guides received an information letter and they were asked for informed
consent. The experiment started when two or three children were gathered to participate. When only one child was available for participation, the B&G attendant/instructor waited with starting the instruction until another participant joined the activity. When two or three children were gathered, the instruction, the time-measurement and the video camera recordings were started.
Every instruction contained the same informative content about stop-motion
animation, the stop-motion animation machine, and ended with the same specific assignment. After the presentation of this assignment – when the children were not already actively busy with the machine yet, the B&G attendant/instructor encouraged the participants to carry out the assignment. During the assignment, the B&G attendant/instructor was allowed to stimulate the participants in three ways: by answering questions, use motivating words for encouragement, and/or by giving hints. These hints were pre-designed and can be found in Appendix D. In line with former research on Creativity, these hints was provided in order to stimulate the participants and make contributions to their feelings of a safe, free, and
supportive environment (e.g. Loveless, 2002; Strom & Strom, 2011). After ten minutes – if the participants were still actively involved with the stop-motion machine, the B&G attendant asked the participants to stop with their activities, whereupon the participants’ productions were viewed and counted together. Following, the participants were asked to answer the researchers’ questions. The survey can be found in Appendix E. After completing this survey, the participants and their parents/guides were thanked for their cooperation, and the children received a small present. All of these characteristics were the same for every condition and are reflected in the measurements. The conditions are further specified in the section below.
The assignment. In order to test the substantive cognitive and creative outcomes of
the research, an assignment was specifically designed. The design was based on
business and academic fields, according to the Board of Regents of the University of
Wisconsin (2007). Based on their research on brainstorming techniques, the focus point of the assignment was quantity. Additionally, a time limit was set in order to create an extra
motivation to perform actively. The specific assignment for current research was: “Create as many stop-animation movies with disappearances as you can within ten minutes”.
Experimental Conditions
Computer-mediated instruction. The computer-mediated instruction (CMI)
consisted of a Power Point (PP) presentation. The presentation was shown on a laptop and the laptop was placed on a table next to the stop-motion machine. A B&G attendant approached visitors actively in order to recruit participants. Next, the participants were asked to take the chairs in front of the laptop, and watch the PP Presentation first. The laptop played the PP instruction automatically with large time-lapses in-between the slides. If preferred, the respondents could enter the space button on the keyboard, in order to view the slides faster. The B&G attendant assisted the children if they could not control the laptop themselves. However, this attendant - apart from the possible encouragements, Q&A-possibilities and hints – did not contribute to the instruction. The PP instruction can be found in Appendix A.
Real life implicit instruction. In the real life implicit instruction condition (RII),
participants received the instruction of an adult instructor. This instructor led the explicit instruction as well, in order to exclude inter-personal instructor bias. The instructor did not have experience with stop-motion animation. However, it was an experienced teacher. Chosen was to test the implicit condition before the explicit, to exclude intra-personal bias: the
possibility of unconsciously adding information from the explicit instruction to the implicit condition.
The implicit instruction was scripted up to and included the assignment. Based on past research on explicit versus implicit instruction and informal learning settings, an informal
setting was created (Bamberger & Tal, 2006). The instructor was clearly present, but did not show clear teaching intentions. Instead, the instructor pretended be in need of with the stop-motion machine. Therefore, children were needed. Next, the instruction script could be started. The script was non-linear; the guide did not start with a clear introduction, but with showing how the machine worked instead. Next, an example was given, but no explicit explanations were given. At the end of the instruction, the instructor presented the assignment. Moreover, the educational value of the exhibit was not mentioned, nor the productive goal stressed. The implicit instruction focused on encouragement, motivating the participants, stimulating analogy learning, and encouraging ownership (Bamberger & Tal, 2006; Beek, 2011; Witt, Puspitawati, & Vinter, 2013).The script can be found in Appendix B.
Real life explicit instruction. On the third experimental day, the impact of real life
explicit instruction (REI) was tested. Again, the instruction was scripted up to and included the assignment at the end. The design of this script was based on earlier research on explicit instruction (e.g. Kemper, Verhoeven, & Bosman, 2012). Consequently, the instructor showed took a clear teacher-role, which stressed the hierarchical teacher-student roles, and features of intentional teaching. The instructor took the lead in the linear format of the instruction. First, stop-motion animation and the machine were introduced. Next, the controls for the machine were explained and an example (the same as in both former instructions; shown in Appendix F) was given. The end of the instruction reflected the assignment. The instructor focused on the educational value of the instruction and stressed the productive goal of the assignment (Kemper, Verhoeven, & Bosman, 2012; Witt, Puspitawati, & Vinter, 2013). This script can be found in Appendix C.
Cognition. Cognitive impact was measured by a 6-item cognitive impact scale,
specifically designed for the purpose of present research. An exploratory factor analysis (EFA) with varimax rotation indicated that the six-item Cognition-scale was
three-dimensional, explaining 60.15% of the variance. The six items measured the cognitive affect of the instruction in three different ways: (1) Substantive knowledge, with two questions concerning information which was given in the instruction. Questions concerned: “What is stop-motion animation?” and “How does the stop-motion animation machine work”. Scores were measured on a 5-point Likert scale – ranging from 1 to 5, indicating the amount of pre-formulated keywords the participants used when giving descriptive answers on the
questions. This variable had a Cronbach’s alpha of .53 (M = 4.15, SD = .11). The scale could not be improved by excluding items. Next, the second dimension of cognitive developmental impact was: (2) Perceived difficulty. This measure consisted of two items concerning the following questions: “Did you think the instruction was difficult?” and “Did you think the activity was difficult?”. Scores were rated on 5-point Likert scales ranging from 1 (= no) to 5 (= yes). Internal consistency was tested with Cronbach’s alpha, resulting in an alpha of .66 (M = 1.47, SD < 0.001). The third cognitive measurement was (3) Necessary guidance. This measure consisted of two questions and indicated the amount of guidance - in senses of (1) the participants’ amount of asked questions and (2) encouragements the participants needed during the performance (α = .66, M = 2.39, SD = 1.03).
Creativity. Creativity was measured distinctly from the general Cognition measures
because of specific emotional affect related dimensions (e.g. intrinsic motivation, Wissink, 2001). In the present study, this resulted in a 13-item scale indicating the creativity of the participants. Based on an EFA with varimax rotation, three dimensions were extracted, explaining 62.8% of the variance. These sub-dimensions were characterized as measurements
for: (1) Substantive creativity, (2) Independent pro-activity and (3) Perceived personal
creativity.
The first dimension, Substantive creativity, indicated substantive results of the instruction. The dimension used six questions to explore the productive activities of the participants. Examples of questions were: “Did the participants imitate the example only or did they make up new possibilities?” and “What kind of materials did the participants use for their productions?”. Scores were rated on a 5-point Likert scale, based on pre-designed possible outcomes. Scores were based on productivity, ranging from 1 (= e.g. ‘The participants did not produce anything new’) to 5 (= e.g. ‘The participants created totally different outcomes than the provided example, with completely other material’). This scale had a reliability alpha of.65 (M = 4.28, SD = .01).
The second dimension of creativity measured Independent pro-activity, and indicated the creative behavior of participants without stimulation of the attendant/instructor. The dimension consisted of four questions. Examples of questions were “How active did the participants behave?”, and “How creatively did they behave independently (without the attendant’s interference)?” Answers were rated on 5-point Likert scales representing pre-designed answers. Scores ranged from 1 (= e.g. ‘The participants only imitated the example’) to 5 (= e.g. ‘The participants did not use the example at all, but created most imaginative solutions themselves’).
The third dimension of Creativity, Perceived personal creativity indicated the participants’ opinion concerning their own creativity. The dimension used three questions, concerning: “What grade would you give your own creativity, in this assignment?”, “What grade would you give your own creativity in general?”, and “What grade would you give the machine for possible creativity stimulation?” Scores were rated on 10-point scales, ranging from 1 (= I am not creative at all) to 10 (= I am very creative). Internal consistency for each of
the scales was examined using Cronbach’s alpha (α = .56 (M = 7.80, SD = 0.03). The scale could not be improved by deleting items.
Appeal. Appeal was measured by an eight-item Appeal-scale. An exploratory factor
analysis with varimax rotation indicated that the scale was three-dimensional, explaining 68.73% of the variance. The sub-dimensions were characterized as: (1) Participants’ reported
enjoyment, (2) Observed enjoyment, (3) Participants’ enjoyment based on time measurements.
The first dimension indicated the participants’ personal view on the likeability of the experiment. Four questions were asked to explore whether the participants thought the instruction and the activity were fun. Examples of questions were: “What grade would you give the instruction” and “What grade would you give the machine?’. Scores were rated on a 10-point scale. This Appeal-sub-dimension showed a good convergent validity as indicated, by the strong correlation with time measurements (r = .90, p < .01). Next, the reliability of the scale met a Cronbach’s alpha of .61 (M = 8.67, SD = .08).
The second sub-dimension of Appeal, Observed enjoyment, indicated the researchers’ view on participants’ enjoyment. The measure consisted of two questions: “Did the
participants show emotions of amusement during the instruction” and “Did the participants show emotions of amusement during the the activity?”. Answers were rated on a 5-point Likert scale ranging from 1 (= Not at all) to 5 (= Very much). The scale showed a reliability of .68 (M = 4.28, SD = .01).
The third Appeal-dimension indicated Participants’enjoyment based on time
measurements and measured participants’ enjoyment by two questions: “Did the participants
listen or watch the whole instruction” and “How long did it last before the participants pro-actively engaged in the activity?”. Items were rated on a 2-point scale ranging from 0 (= No) to 1 (= Yes) and a 4-point scale ranging from 1 (= Up to the introduction of the machine, then
they were not interested anymore) to 4 (= They heard/viewed the whole instruction). This scale had a reliability alpha of .73 (M = 2.43, SD = 4.33).
Qualitative Measures and Video Analysis
Additionally to the quantitave measures, two qualitative items were added to the survey in order to gain more in-depth insights of participants’ views on their own creativitiy, and ideal creativity stimulating settings of the museum. Results of these questions were compared and matched (if possible) with the outcomes of the quantitative measures.
Additionally, video recordings were analyzed and categorized based on interesting aspects. If possible, results of both additional research methods were tried to be matched with the quantitative results of the present research.
Results Time Spent on Activity
In order to explore significant differences between the time spent on the activity in the different conditions, a one-way ANOVA was performed. Results showed that there was a significant difference between the experimental conditions when it comes to the time children spent on the assignment (F (2, 84) = 3.24, p = .04). Participants spent significantly more time in the real life explicit instruction condition (M = 5.73, SD = .83) than in the implicit- (M = 5.10, SD = 1.17), and the computer-mediated condition (M = 5.08, SD = 1.35).
Additionally, correlation analyses were performed to test the relation between Time
spent on the activity and the most relevant dependent variables of the present research: Substantive knowledge gain, Substantive creativity, Observed enjoyment, and Participants´ reported enjoyment. The first three relationships – Time spent on the activity and Substantive knowledge gain; Substantive creativity; and Observed enjoyment were all significant with
correlations of respectively: r = .40, p < .001, r = .25, p = .02, r = .39, p < .001. This indicates that the amount of time participants’ spent on the activity was related to participants’
substantive cognitive development, their creative behavior and the researchers´ view on participants’ enjoyment. However, the relationship between the time participants’ spent on the activity and their own reported enjoyment was not strong enough to state that those aspects correlated.
Additionally, analyses of the video recordings showed that the children were enthusiastic to engage in the stop-motion animation activity in every condition. Large differences were not detected. Video recordings showed e.g. one child saying “I’m not yet finished, the shark still has to disappear”. Moreover, qualitative questions proved that several children answered “If I would have had more time” on the researchers’ question how they thought they could have been more creative than they had been now.
An overview of the main differences between the different instructions and their effects on the sub-dimensions of Cognition, Creativity, and Appeal are shown in Table 1.
Table 1 Main effects of the different instruction methods
Condition Mean CMI
(SD)
Mean RII
(SD)
Mean REI
(SD)
Mean Real life
(SD)
Score time spent 5.08 (0.80) a, b 5.10 (0.92) a , b 5.73 (0.77) a , b 5.41 (1.06)
Substantive knowledge 3.77 (1.25) a, b 3.56 (.71) 5.26 (1.45) 4.31 (.67) a, b
Perceived difficulty 2.21 (1.31)a , b* 1.16 (.51) 1.15 (.40) 1.16 (.45)a , b*
Necessary guidance .87 (.87)a , b* 3.13 (.98) 2.95 (1.48) 3.01 (1.25)a , b*
Substantive creativity 4.02 (.82) 3.56 (.71) a , b* 5.26 (1.45) a , b* 4.40 (1.41)
Independent pro-activity 4.38 (.55) 4.16 (.60) 4.31 (.62) 4.23 (.61)
Perceived personal creativity 7.97 (1.22) 7.56 (1.40) 7.89 (1.37) 7.72 (1.38)
Respondents’ reported enjoyment 8.85 (.50) 8.63 (.80) 8.53 (1.06) 8.58 (.93)
Observed enjoyment 4.12 (.55) 4.39 (.53) 4.30 (.53) 4.34 (.50)
Appeal based on time 5.35 (1.02) 5.35 (.93) 5.57 (.80) 5.55 (.88)
Note: CMI = Computer Mediated Instruction, RII = Real Life Implicit Instruction, REI = Real Life Explicit Instruction.
Values in rows with identical superscripts (a , b) differ significantly at least p < .05. Values in rows with identical superscripts (a , b*) differ
Cognitive Effects
Substantive knowledge. In order to explore the impact of instruction on Substantive knowledge between the REI - and RII conditions, an independent samples T-test was
performed. This test compared the effect of both real life instruction methods on the
substantive cognitive development of the children. Although the difference was not far from significant (t (59) = -5.87, p = 0.05(4)), different effects of REI or RII on Substantive
knowledge was not proven. On the contrary, an independent samples t-test showed that there
was a significant difference measured between the real life conditions and the computer-mediated conditions. Children could reproduce significantly more substantive information from the instruction in the real life instruction conditions than from the instruction in the computer-mediated condition (t (31.2) = -2.09, p = .05). This indicates that children gained substantively more knowledge in the real life instruction conditions than in the computer-mediated condition.
Perceived difficulty. An independent samples T-test was used to explore whether
there was a significant difference in the Perceived difficulty between the computer-mediated- and the real life conditions. Results show that there was a significant difference between the reported difficulty children experienced in the computer-mediated instruction in comparison to the real life instructions. Participants perceived the experiment significantly more difficult in the computer-mediated condition than in the real life conditions (t (27.6) = 4.01, p < .001). On the contrary, results of an independent t-test between computer-mediated instruction and real life instruction on Guidance needed showed that children verbally demonstrated a higher need of guidance in the real life instruction conditions (t (85) = -8.10, p < .001). Additionally, video analyses showed that children focused more on the real life instructor in the REI- and in the RII-conditions, than on the attendant in the CMI-condition. Results show that children were tempted to address the instructor(s) more than the attendant. Children were more passive
and waited longer before asking guidance in the computer-mediated condition. Summarizing, children reported that they experienced the computer-mediated instruction as more difficult, but showed verbally a bigger need of guidance in the real life conditions.
Creativity
Substantive creativity. In order to investigate whether the real life instructions
impacted Substantive creativity differently, an independent samples T-Test was performed. Results show that the participants’ substantive creative behavior was more prominent in the explicit condition than in the implicit condition (t (59) = -5.87, p < .001). The video analyses confirmed this statement. After the presentation of the assignment in the explicit instruction, the children were more proactively engaged within the activity compared to their behavior in the implicit instruction condition. As results show, the explicit instruction led to significantly more creative behavior than the implicit instruction.
Additionally, there were no significant differences found in creative productive behavior between the computer-mediated and the real life conditions taken together nor apart from each other. Although explicit instruction led to significantly more creative behavior in comparison to computer-mediated instruction, and in comparison to the difference between
Substantive creativity between implicit instruction and computer-mediation, did this first
difference not lead to significant results.
Appeal
Respondents’ reported enjoyment. In order to measure the impact of instruction on
the Respondents’ reported enjoyment, an independent samples t-test was performed. Results show that there was no significant difference between explicit instruction and implicit real life instruction. Additionally, children reported higher feelings of enjoyment in the computer-mediated condition compared to the real life instruction conditions. However, these differences did not prove to be significant.
Observed enjoyment. An independent t-test was used to explore the differences
between implicit and explicit instruction on the participants’ observed enjoyment, as rated by the researcher. Results showed that no significant differences between the different instruction methods. In addition, the differences between the effects of computer-mediated instruction and real life instruction on Observed appeal were larger. Although not far from significant (p = .06) – children in the real life instruction condition were rated as slightly more
entertained by the activity than computer-mediated instruction, the results did not prove to be significant.
Discussion
The present study aimed to examine the impact of instruction on the substantive cognitive development and creativity of children, and their socio emotional appeals. Three different instruction methods were tested in a quasi-experimental design in order to find an answer to the main research question. A media oriented museum was used as location, and a specific exhibition item was chosen to test the impact of respectively real life explicit
instruction, real life implicit instruction, and computer-mediated instruction on cognitive- and creative development, and on children’s enjoyment.
Based on previous research on the impact of instruction, the following hypotheses were formulated: (H1) The explicit instruction will yield more substantive knowledge than the
implicit instruction, (H2) The implicit instruction will appeal to children more than the explicit instruction, (H4) The computer-mediated instruction will stimulate the substantive cognitive development of the children more than the real life instruction, (H5) The computer-mediated instruction will stimulate the creativity of the children more than the real life instructions, and (H6) The computer-mediated instruction will appeal more to children than the real life instructions.
Substantive Knowledge: Explicit Versus Implicit Instruction
Based on the results of previous research, it was expected that the explicit instruction would yield more substantive knowledge development compared to an implicit instruction method. Although results showed that the explicit instruction did lead to more substantive knowledge than the implicit instruction - and the differences were not far from significant, hypothesis 1 was not supported by significant outcomes.
Previous research showed opposing results. Explicit instruction could be more effective in yielding deeper and broader substantive cognitive development, due to raised awareness after explicit instruction (Damhuis, Segers, & Verhoeven, 2014). Results of past
research showed support for positive short-term and long-term effects of explicit instruction on knowledge gain, even for children in the kindergarten-age (Witt, Puspitawati, & Vinter, A, 2013; Damhuis, Segers, & Verhoeven, 2014). Although the results of the present research are not (significantly proven) in line with those outcomes, did the explicit instruction yield more substantive cognitive development than the implicit – and the computer-mediated instructions. Due to the limited amount of available time for the learning activity in the museum, and the lack of real in-depth informative content within the instruction, it might be possible that the activity cannot be considered equal to formal educative activities, and therefore to research on the effects of explicit informative instruction in school settings. Effects could have reached ceiling levels before children could really take advantage of the method used in the explicit instruction condition. A longer time span and more in-depth informative content in the instruction could possibly have led to more and larger differences between the different instruction conditions.
Creativity: Explicit versus Implicit Instruction
Hypothesized was that the implicit instruction would stimulate the development of the complex cognitive skill Creativity more than explicit instruction. Surprisingly, the results of the present research show support for an opposing hypothesis. Children showed significantly more creative behavior in the explicit instruction condition compared to the implicit
instruction condition. Children produced more items, and more varying products in the explicit instruction condition, in comparison with the implicit instruction condition. Therefore, hypothesis 2 is not supported. Although this outcome contradicts literature on explicit versus implicit instruction - which argued that looser instruction methodologies would stimulate learners’ creativity more due to raised levels of experienced control, engagement, and freedom (Loveless, 2002; Strom & Strom, 2011), results do happen to be in line with previous research on brainstorming techniques (University of Wisconsin, 2007). The research
on brainstorming showed that an explicit focus on quantity stimulates and triggers individuals to produce as many and as many different products as possible (Board of Regents of the University of Wisconsin, 2007). Apparently did the instructor’s explicit focus on the assignment, quantity and a limited time-span stimulate children’s creativity more than the
Creativity-stimulating characteristics of the implicit instruction did.
Appeal: Explicit- versus Implicit-, and Computer-Mediated Instruction
Results of present research pointed out that the variation in instruction methods did not impact children’s feelings of enjoyment in any way. There were no significant differences found between appeals in the explicit versus the implicit real life condition, nor in comparison to the computer-mediated instruction. On average, the activity, the instructor, the assignment and the actions of the machine, were rated as very appealing. Children were very enthusiastic about every aspect of the exhibition item and the activity. These results contradict earlier research and the formulated hypotheses 3 and 6, which stated that children would value implicit instruction more than explicit-, and computer-mediated instruction more than real life instructions.
As previous research showed, individuals tend to rate implicit instruction methods as more appealing due to experienced freedom, raised levels of experienced self-control, resulting in more feelings of engagement with educational content, triggered proactive learning behavior, and elicited intrinsic motivation (Vermunt & Verloop, 1999; Beek e.a., 2011). However, since all three conditions met these characteristics of relative freedom; children could do with the machine and the additional tools whatever they wanted; and there was a lack of rules and absence of limits (besides time-). These circumstances might have led to a minimal difference between the different instruction conditions; children might have experienced the same high levels of enjoyment in every condition of the museum instruction.
This would also be in line with research of Anderson e.a. (2002) on museum
experiences. They argued that museums are ideal settings for playful learning due to the broad range of circumstances which impact visitors in many ways, e.g. the overall outlook, items, graphics, colors, sounds etc.. Anderson e.a. (2002)’s research showed that museum visiting children showed enjoyment due to a variety of reasons. Not every child might like the same features and things to do or see, but there always seems to be something children really enjoy seeing or doing in a museum (Anderson e.a., 2002). This might have happened in the present research as well; the sum of different appealing aspects created an overall enjoyable
experience for many of the participants, without significant differences.
Next, when it comes to the instruction’s content, the conditions were all characterized by features which proved to be very appealing to children in previous research. The computer-mediated instruction contained graphics, visuals and sounds which are things children
appreciate (Vernadakis e.a., 2002; Brunken, Plass, & Leutner, 2003). However, many of these features were recognizable in the real life instructions too. Next, as previous research showed, did the interactive component of real life instruction contribute to children’s appeals too (Missildine e.a., 2013). Although this feature was seemingly absent in the computer-mediated instruction, it was also present in this condition due to the attendants’ guidance. Bigger differentiating characteristics between the instruction methods might have led to bigger differences.
Substantive cognitive development: Computer-mediated versus real life instruction
Predicted was that the computer-mediated instruction would benefit the cognitive development of children more than real life instruction. Analyses showed the opposite: the computer-mediated instruction led to significantly less substantive cognitive development than the real life instruction conditions taken together. Moreover, the difference between implicit instruction and computer-mediated instruction was not significant, whereas explicit
instruction did lead to significantly more cognitive development than computer-mediated instruction. In addition, although participants asked the attendant for more support and answers on questions (which often indicates experienced difficulties), difficulty ratings show that children rated the computer-mediated instruction as significantly more difficult than the real life instructions. Apparently those feelings did not lead to more questions or verbally uttered need of support.
The results can be explained because – as previous research showed that, children are stimulated most by interpersonal communication (Missildine e.a., 2013). The computer-mediated instruction clearly triggered more passive, waiting behavior, whereas real life instruction stimulated the interpersonal communication between the instructor(s) and the participants. This resulted in more questions from the participants and interactivity between the instructor and the learners. Apparently, these features stimulated the participants’ activities, and encouraged them in their cognitive development.
Next, although researchers argued that computers trigger learners’ learning processes due to their flexibility and capacities (Kong e.a., 2014), and children are more and more used to computers in classical learning settings, which enhances their developmental speed; this is not necessarily the same in an informal learning setting such as a museum. Children might not even have considered the computer-mediated instruction as a learning experience. Moreover, children consider museum visit on average not as learning experience either (Anderson e.a., 2002). The children might not have recognized the educative setting, nor have linked it to pre-knowledge from school or home. Moreover, children might have gained pre-knowledge on other aspects than the content of the measurements of the present research. As supported by Anderson e.a. (2002), the things children learn, and their experiences in museums are very personal. Additionally, those preferences were not necessarily in line with what the present research aimed to educate. As a result, hypothesis 4 is not supported by the present research.
Creativity: Real Life Instruction versus Computer-mediated instruction.
Hypothesized was that computer-mediated instruction would trigger learners’ creativity more than real life instruction, as museums are widely acknowledged as ideal creative, imagination triggering environments (Donald, 1990; Anderson e.a., 2002; Bamberger & Tal; 2006). Results of the present research show no support for this belief. However, museums might not always be recognized as environments to be creative (Anderson e.a., 2002; Bamberger & Tal; 2006; Ballofet, Courvoisier, & Lagier, 2014). Although children showed slightly more substantive creativity in the computer-mediated condition compared to implicit real life instruction; explicit instruction elicited more substantive creative behavior of children than the computer-mediated instruction. This might have been due to the stressed formulation, and the focus on quantity and a limited time-span (in line with the brainstorm technique of Board of Regents of the University of Wisconsin (2007). The effects of this design might have out ruled the effects of the features of the museum. Therefore, hypothesis 6 is not supported by results of the present research.
Limitations & Future Research
The present research was limited through a variety of aspects. First of all, the age range of the participating children (4-15 years old) might have biased results due to the fact that – as several developmental psychologists pointed out (Bukatko, 2008); children develop roughly in the same way. However, children develop very fast and there are many differences between the developmental phases of children between four and fifteen years old. This could have strongly impacted results of the present research. A narrower age domain could have resulted in more clear results due to the belief that children of the same ages show more similarities.
Additionally, a larger amount of time for the activity could have led to more variance in creative outcomes, and therefore may have reduced possible ceiling effects. As Strom and
Strom (2011) stressed, creativity is most triggered in free, limitless, timeless settings.
However, the present research used a time limit of ten minutes, which could have limited the creative behavior of the participants. However, on the other hand, the time limit could also have benefited the creativity of the participants. As the board Wisconsin Board of Regents (2007) argued, time limits benefit brainstorms due to experienced pressure and a stronger drive to perform, innovate, and produce. Due to the limited amount of time for the research, and the choice for a focus on quantity in the assignment in order to measure specific features of Creativity, the present research chose to limit the activity time to ten minutes (Loveless, 2002; Wisconsin Board of Regents, 2007).
Moreover, the relative low reliability of the measurements could have biased the results of the present research. Consequentially, they could have lowered the reliability of the outcomes. Unfortunately, exclusion of questions did not lead to higher reliability alphas. In order to improve the reliability of the research, measurements could have been revisited, pre-tested, and re-tested. However, due to limited amount of available time, this was not possible.
Additionally, the choice to use a specific exhibition item might have biased the results of the research due to the restricted setting. As a result, individual preferences might have had large effects on the outcomes, as shown in Anderson e.a. (2002). If children had a stronger preference for other aspects of the museum, specific features of the exhibition item or the assignment than the focus points of the present research this could have had a large effect on the results. Next to that, the choice for B&G as location could also have affected the results due to individual preferences or interests. In order to draw more conclusions on the impact of the museum on the results, questions specifically focusing on the museum should have been added to the measures. However, it does contribute to existing literature on children’s museum experiences since this was most-often limited to science centers (Anderson e.a., 2002).
Finally, the guiding instructor or attendant could have biased the results due to inter-personal effects with participants. This effect could not be excluded. The effect was tried to be limited by the use of scripted instructions and the same instructor in the real life explicit – and the implicit conditions. However, since research on instruction was most-often limited to school-related areas, the present research made a contribution to research on instruction in informal educational settings, and more specifically: a museum setting. Although results did not prove to be significant, the different methods of instruction showed that children
responded differently to varying methods of instruction.
Re-formulation of the research measurements, pre-testing, re-testing, qualitative research and more time could make important contributions to research on the present topic of interest. Consequently, results could contribute to the formulation of advice for museum professionals on instruction use, exhibition development, -design, and unforgettable museum experiences for children.
Conclusion
Research on instruction is most-often limited to schools. The present research aimed to explore the effects of different kinds of instruction on children’s museum experience. The focus was set on the impact of explicit real life instruction, implicit real life instruction, and computer-mediated instruction, and their effect on children’s substantive cognitive
development, creativity, and enjoyment. This research question was tested in a quasi-restricted area of a museum, using a specific exhibition item, and a clear assignment. In December 2014, 92 children (aged 4-15) participated in present quasi-experimental study. Results showed that, although the results were not far from significant, different instruction methods did not lead to substantively more knowledge. Explicit instruction showed most beneficial effects for cognitive development and creative stimulation of children, compared to the effects of the implicit instruction and the computer-mediated condition. Next, real life instruction led to more pro-activity, interactivity, and explicit need of guidance than computer-mediated instruction. Computer-mediated instruction was experienced as most difficult. More research on instruction in museum settings is needed in order to provide
museum professionals recommendations on the use of varying instruction methods in museum designs.
The present research concludes that museums could benefit from implementing instruction in their exhibition, or within specific exhibition items. By strategic use of instruction, children’s museum visits could get an unforgettable twist with surprisingly creative outcomes - even for museum professionals.
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Appendix A: Computer Mediated Instruction
In de computer gemedieerde conditie wordt de instructie ‘geleid’ door een
computerpresentatie in de vorm van een Power Point presentatie. De computer-gemedieerde instructie is bijgevoegd in de bijlage en als video te bekijken op:
http://youtu.be/2ygzbOJe3Rc.
De presentatie wordt getoond op een laptop, waarbij de kinderen zelf de spatiebalk kunnen bedienen. Indien dit een probleem is bedient de onderzoeken ofwel de PBG de ppt. Voorbeeldfilmpjes worden getoond op de iPad van B&G. Als er 2 á 3 kinderen ‘verzameld’ zijn begint het experiment met de start van de Power Point presentatie. Onderstaand de slides van de ppt.
Appendix B: Implicit Instruction Script
1. [Setting] In de impliciete instructie-conditie zit de publieksbegeleider met de stop-motion machine te ‘spelen’. Uiterlijk publieksbegeleider hetzelfde (zelfde persoon) maar minder overheersend aanwezig dan in conditie 1.
2. [Inleiding, wanneer er kinderen langslopen] Hoi, zouden jullie mij ergens mee willen helpen? Ik wil hiermee (wijst naar apparaat) graag een filmpje maken. Maar het lukt niet. Wil jij me helpen? (Bij één kind wachten op nog een participant). 3. [Non-lineair verloop] Kijk, Ik zou graag iets willen laten verdwijnen. Deze
machine kan foto’s maken. Kijk als ik hier wat neerzet, maak ik zo een foto. Probeer de knoppen zelf maar ‘ns. Kijk als ik heel vaak druk en dit doe (poppetjes eventjes bewegen) en daar druk (op computerknop voor afspelen) dan heb ik ineens een film. Zo kan de film worden afgespeeld.
4. [In-direct Assignment, Encourage Ownership] Maar, nou wil ik iets laten verdwijnen. Kunnen jullie me helpen?
5. [Encourage Ownership ]Volgens mij kunnen jullie dat veel beter dan ik. 6. [Motiveer] We mogen ALLES gebruiken wat hier ligt.
7. [Motiveer] Ik weet zeker dat jullie dat heel goed kunnen. Probeer maar wat. 8. [Na afronding 1 filmpje. Motiveer] Jullie kunnen vast nog veel andere manieren
om iets te laten verdwijnen verzinnen.
