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Affect trumps age: A person-in-context relational view of age and motivation in
SLA
Simone E Pfenninger
(English Department,) University of Zurich, Switzerland
David Singleton
(Institute of Applied Linguistics,) University of Pannonia, Hungary
Corresponding author:
Simone E. Pfenninger, English Dept., University of Zurich, Plattenstrasse 47, 8032
Zurich
E-mail: simone.pfenninger@es.uzh.ch
Affect trumps age: A person-in-context relational view of age and
motivation in SLA
Abstract
Recent findings (see e.g. Muñoz and Singleton, 2011) indicate that age of onset is not
a strong determinant of instructed foreign language (FL) learners’ achievement and
that age is intricately connected with social and psychological factors shaping the
learner’s overall FL experience. The present study, accordingly, takes a participant-
active approach by examining and comparing L2 data, motivation questionnaire data,
and language experience essays collected from a cohort of 200 Swiss EFL learners at
the beginning and end of secondary school. These were used to analyze (1) whether
in the long run early instructed FL learners in Switzerland outperform late instructed
FL learners, and if so the extent to which motivation can explain this phenomenon,
(2) the development of FL motivation and attitudes as students ascend the educational
ladder, (3) the degree to which school-level variables affect age-related differences,
and (4) learners’ beliefs about the age factor. We set out to combine large-scale
quantitative methods (multilevel analyses) with individual-level qualitative data.
While the results reveal clear differences with respect to rate of acquisition in favor of
2
the late starters, whose motivation is more strongly goal- and future-focused at the
first measurement, there is no main effect for starting age at the end of mandatory
school time. Qualitative analyses of language experience essays offer insights into
early and late starters’ L2 learning experience over the course of secondary school,
capturing the multi-faceted complexity of the role played by starting age.
Keywords
Age factor, motivation, multilevel modeling, learner beliefs, context variables
Introduction
In recent decades, it has become increasingly apparent that factors of a social,
psychological and contextual nature are prominent in both early and late second
language (L2) learners in naturalistic settings as well as classrooms (cf. Moyer
2014a). However, so far only minimal attention has been paid to the interaction
between person and context in quantitative and qualitative age research. One reason
for this is the limited availability of convenient and successful methods for addressing
context effects statistically. Another challenge is mentioned by Moyer (2014b), who
3
suggests that since age of onset (AO) has a significant relationship with experience,
the nature of that relationship needs to be clarified in future research via the
‘messiness’ of introspective methods (458). In conformity with this view, Pica (2010)
points out that the heavy emphasis on age in making decisions about school policy
and practice has overlooked the abundant research on psychosocial factors such as
learner beliefs and motivation that have been shown to impact on language learning
in a school context and which may explain why “early L2 schooling is not necessarily
better” (260). Thus, whilst learners’ ultimate levels of achievement and proficiency
will remain a focus of age-related research, an important additional perspective needs
to focus on the processes and timescales in which learners can be seen to be happy
and experience flourishing in language learning, as well as situations in which they
struggle with boredom or with challenges that demand more of them than they are
capable of delivering.
This article focuses on methodological advancements in the area of AO and
motivation in the classroom by combining large-scale quantitative methods that give
an account of both participant and item variability with individual-level qualitative
data. Multilevel analyses are performed to investigate to what extent late starters’
long-term achievement in instructional settings matches the supposedly advantaged
4
performance of early starters. Also analyzed is how motivation factors into this
process. In order to capture psychological elements of learning English as a foreign
language (EFL) from different ages and on different levels internal to the learner ––
language experience essays produced by the participants are drawn on. These help
identify aspects of early and late EFL instruction that seem salient to particular
individuals at the beginning and at the end of secondary school, and thus help
constrain the influential factors other than age that play a role in L2 development.
Such a holistic approach takes into account the combined and interactive operation of
different elements/conditions relevant to specific situations, rather than following the
traditional practice of examining the relationship between well-defined variables in
relative isolation. This approach can also, we believe, provide a richer picture of the
interaction of AO and other (often hidden) variables (see Muñoz, 2014a) than an
approach solely focusing on learners’ long-term outcomes as a function of AO.
An ecological approach to age
Age-in-context I: Cohort effects on motivation
It has been well-documented that the localized practices, experiences and histories of
learners in particular classrooms are pivotal in shaping the process of L2 learning
5
motivation and performance. Since individuals are known to accommodate to the
normative environment within their class setting, changes in an individual’s
motivational state are thought to be the result of sustained exposure to and
observation of peers, a process commonly referred to as “modeling” (e.g. Berndt and
Keefe, 1995). Learners observe and assess the motivational states of their peers and
may gravitate to the group norm. They may well influence each other in their
perceptions and in their orientation to the classroom environment. In her theory of
group affective tone, George (1995) posits that groups, over time, develop a tendency
to display collective mood states. Positive group affect, for instance, can lead to
increases in motivation and “spreading goodwill” during interpersonal encounters
(George and Brief, 1992: 310). According to Forsyth (2010) group orientations can
also change the way group members think about themselves (see also Mercer, 2014;
Sedikides and Brewer, 2001). Since most people’s selves are a combination of both
personal and collective elements, their answers to the question, “Who am I?” in time
will thus change to include more collectivistic elements.
Peers also influence each other with respect to the value they place on the
development of L2 proficiency. As they do so, their own motivational state may
become dynamic and may eventually lead to greater or lesser gains in L2 proficiency
6
over time. For instance, Kozaki and Ross (2011) examined the clustering effects of
streamed classes in a foreign language (FL) program and found class compositional
effects to exert both ameliorating and constraining effects on proficiency growth. The
class compositional effects – perceived peers’ normative aspiration to professional
pursuit and orientation to the social mainstream – mediated the trajectories of
individual differences in growth of proficiency. The results of the study suggest that
peers can exert a normalizing influence in FL classrooms that can augment or
undermine individual learners’ own motivations to learn the FL.
Individuals in a school context are influenced not only by their peers but also
by the circumstances of the learning environment. Chaudron (2001) suggests that
classroom processes are heavily influenced by the structure of classroom
organization. Different patterns of teacher-student interaction, group work, degrees of
learners’ control over their learning, and variations in tasks and their sequencing are
seen to play a significant role in the quantity and quality of learners’ production of
and interaction with the target language. Similarly, intensity of teaching and small
groups are found to be conducive to positive attitudes in young learners (e.g. Vilke
and Vrhovac, 1995). Given all this, it is not surprising that students within a
classroom have been found to be more similar to each other than to students in other
7
classrooms due to whatever school level characteristics are measured (Seltman, 2009:
375).
From a theoretical and research perspective, these arguments place a premium
on classroom-focused empirical studies which investigate how learning contexts
shape processes of motivation and L2 proficiency in individual classrooms (see also
Ushioda, 2013). In the field of individual differences in SLA, for instance, Dörnyei
(2005) has suggested that research should seek to focus on particular constellations
where cognition, affect and motivation function together as wholes. Because most L2
learning in EFL settings happens in institutional environments, the age factor also
needs to be considered in the light of macrocultural and microcultural phenomena
having a bearing on interpersonal relations; these may influence and shape the
motivational states of individuals and groups. The importance of contextual factors in
age research is recognized in research which has highlighted the significant effect of
the ‘macro context’. For instance, it is observed that instructional conditions lead to
different age-related results from natural exposure conditions (see e.g. the reviews in
Lambelet and Berthele, 2015; Muñoz and Singleton, 2011; Singleton and Ryan,
2004). Numerous classroom studies in Europe and across the world have yielded
consistent results showing not only a rate advantage for late starters over early
8
starters but also very few linguistic advantages to beginning the study of an FL earlier
in a minimal input situation (see e.g. Al-Thubaiti, 2010 for Saudi Arabia; Muñoz,
2006, 2011 for Catalonia (Spain); Larson-Hall, 2008 for Japan; Myles and Mitchell,
2012 for Great Britain; Pfenninger, 2013, 2014a, 2014b for Switzerland; Unsworth et
al., 2012 for the Netherlands).
Age-in-context II: Interaction of age and individual difference variables
The age factor also interacts with social-psychological, personal and affective
variables (see e.g. Moyer, 2014a, 2014b). In the realm of L2 learning motivation,
Dörnyei currently considers vision to be one of the highest order motivational forces,
allowing the consideration of motivation as a long-term, ongoing endeavor (see e.g.
Dörnyei, 2014; Dörnyei and Kubanyiova, 2014). A strong future vision of L2 success
is a reliable predictor of students’ long-term intended effort and overall perseverance,
which are necessary to bring them to high ultimate attainment. Along similar lines
Ryan and Irie (2014) emphasize that “possible selves … contain an element of
experiencing ourselves in that future state” (113). More importantly, it has often been
reported that younger school learners are more motivated and have a more positive
attitude towards a foreign language than older school learners, and that this is a
9
definite advantage of an early start (e.g. Blondin et al. 1998; Edelenbos et al., 2007;
Hawkins, 1996), although the opposite has also been found (e.g. Dewaele and
MacIntyre, 2014). However, Muñoz (2008) cautions against confounding biological
age and age of onset when it comes to young learners’ attitude: the finding that
younger starters have a more positive attitude towards learning a second language
than older starters may be a result of their younger chronological age rather than or in
addition to their earlier start. Also important is the fact that social-psychological,
personal and affective variables may be under the influence of the more local learning
situation. For a statistical model in age research this means that, e.g., students who
are nested within classes within schools cannot – must not – be treated as independent
observations, as the errors of measurements are not independent. Furthermore, recent
thinking on age (see e.g. Singleton and Pfenninger, 2015) suggests that external
factors such as classroom effects also need to be addressed, as environmental
influences interact with age effects and possibly mediate them. What is more, if
inadequate attention is paid to the unit of analysis (students, class groups, teachers, or
schools), differences found in the dependent measures may be due to uncontrolled
differences among the participating groups rather than the main independent variable
(in the present case, age of onset of learning). Filtering out or failing to address
10
external influences would thus be a gross error of omission. However, the use of
general linear models such as ANOVA, t-tests, single-level regression, c2-tests, etc.,
which require prior aggregation and are run on the averaged data, is still widespread
in age-related research in SLA. These models cannot take account of the various
unmeasured aspects of the upper level units (e.g. schools or classrooms) that affect all
of the lower level measurements (e.g. measurements within subjects or students
within classrooms) similarly for a given unit. Accordingly, a t-test (or, equivalently,
an ANOVA) may well yield a statistically significant result when there is, in fact, no
effect (e.g. for starting age). It is thus high time for age researchers to begin to
employ models that permit the study of inter-and intra-individual variability across
situations and across time with a more careful parsing of variance between persons
and between items and thus have built-in ecological validity. Such an approach is
multilevel modeling (MLM), which is proposed in this article.
Research questions
The following research questions are addressed in this study:
11
(1) Do early instructed FL learners in Switzerland outperform late instructed
FL learners in the long run, and if so to what extent can motivation explain this
phenomenon?
(2) How do FL motivation and attitudes towards learning of EFL develop as
students ascend the educational ladder in secondary school?
(3) To what extent do school-level variables affect age-related differences?
(4) How do beliefs about the age factor vary among EFL learners with
different AOs?
Note that in our study, “long term” refers to attainment at the end of mandatory
schooling in Switzerland (but cf. Muñoz, 2008, 2014b). By school-level variables we
mean context variables, which include, for example, school location and resources,
and climate variables, applied to characteristics of the learning environment (e.g.
class size, learner expectations, motivation, attitudes, beliefs, influence of teachers
and parents, etc.). With all of this in mind, we opted for an equal-status sequential
mixed methods design, where the rationale was that of complementarity, development
and triangulation (described in detail in Pfenninger and Singleton, 2015). We thus
focus not only on FL motivation and learners’ beliefs as individual difference
12
variables but on particular students who are engaged in language learning. On the
practical side, we seek to outline a way of researching the age factor in SLA that
accommodates the multifaceted nature of this variable, with a special emphasis on the
crucial mediating role that clustering effects and individual characteristics and beliefs
play. Note, however, that we do not here attempt to provide a detailed account of
research designs, methodologies and instruments for investigating the age factor. The
focus is on the conceptual basis of the models in question.
Several data collection instruments were deployed in the study: (1) six L2
proficiency tasks; (2) one language experience essay (composed in the learners’
language of literacy, that is, Standard German); and (3) one questionnaire that
mapped students’ general motivational dispositions at both data collection times.
Method
Participants
Our participants were 200 secondary school students from the German-speaking part
of Switzerland, who were tested at the beginning and at the end of academically
13
oriented high school when they were 13 and 18 years old respectively. 100 of them
were early classroom learners (henceforth ECLs) of English who had started being
instructed in the language in early childhood (AO 8), and the other 100 were late
classroom learners of English (henceforth LCLs) who had started being instructed in
the language around puberty (AO 13) – see Table 1:
Table 1. Subjects participating in the study.
Grou
pNumber
of
subjects
Age at
time of
testing
(mean)
Age of
onset
(year of
starting
EFL)
Length of
instruction
in years
Length of
instruction
in hours
ECL1100 13-14
(13;8) 8-9
(2) 5.5 440
LCL1100 13-14
(13;4) 13-14
(7) 0.5 50
ECL2100 18-19
(18;8) 8-9
(2) 10.5 1,170
LCL2100 18-19
(18;9) 13-14
(7) 5.5 730
Note: ECL1 = early classroom learners at Time 1; ECL2 = early classroom learners at Time 2; LCL1 = late
classroom learners at Time 1; LCL2 = late classroom learners at Time 2.
The two groups were controlled for L1 (Swiss German), additional FLs learned
(Standard German, French), SES, teaching method and weekly hours of EFL
14
instruction received. Early starters were not mixed in the same classes as late starters.
The 200 learners were nested within 12 classes that were nested within five schools in
the canton of Zurich. One out of the four schools was in a suburban area, while the
others were in urban school districts.
Note that, despite its status as a language of literacy, Standard German is
considered an L2 here: while Swiss German is a High Alemannic variety of German,
it is hardly understandable to someone who knows only Standard German, as the two
languages differ considerably in lexicon, phonology and syntax (see e.g. Berthele,
2010). According to Lüdi (2007, p. 161), most Swiss citizens are monolingual in
childhood, becoming bilingual in the early primary grades when they receive formal
literacy training in L2 German from 1st grade on (age 7). This means that German-
speaking Swiss children have to learn a relatively unknown language. The situation is
similar regarding French: although one of the four national languages of Switzerland,
it is considered a foreign language in this study because children in Zurich grow up
monolingual, speaking Swiss German, and learn French exclusively in school.
For the qualitative analysis, we selected a focal group of 20 early learners and 20
late learners from those 200 who had participated in the quantitative phase. Early and
late learners were selected according to scores on a range of L2 proficiency tests
15
administered at Times 1 and 2. Following Muñoz (2014a), the criterion for inclusion
in the high achievement groups was a score in the 75th percentile on all tasks, and for
inclusion in the low achievement groups a score in the 25th percentile on all tests.
Furthermore, the high-achievers all had grades at or above 5 (6 being the highest
grade). Following these grouping criteria, we ended up with four groups of 10
participants: 10 early learners, high achievement (ELH); 10 early learners, low
achievement (ELL); 10 late learners, high achievement (LLH); and 10 late learners,
low achievement (LLL). This enabled us to study the most successful learners vs. the
least successful learners in the sample.
L2 proficiency tasks
Language data were collected by means of a test battery that included a standardized
listening comprehension task (see Pfenninger, 2014a, 2014b), two written
compositions (an argumentative and a narrative essay), a grammaticality judgment
task,1 a vocabulary size test (Academic sections in Schmitt, Schmitt and Clapham’s
(2001) Versions A and B of Nation’s Vocabulary Levels Test), Laufer and Nation’s
(1999) Productive Vocabulary Size Test, and two oral tasks (the re-telling of a silent
1 The reliability coefficient (KR-20) obtained was .90 for grammatical items and .95 for ungrammatical
items.
16
movie and a spot-the-difference task). The grammaticality judgment task included
morphosyntactic structures that have been found to be particularly age-sensitive, such
as articles and inflections, as well as structures that are not particularly age-sensitive,
for instance word order and do-support (see e.g. McDonald, 2006). We applied two
different analyses to the data from the spoken and written production tasks in order to
answer research question (1): (a) a communicative holistic analysis, and (b) a
quantitative analysis. For the holistic evaluation of the English and German essays,
we partly followed Jacobs et al.’s scale (1981), which, according to Lasagabaster and
Doiz (2003: 140), requires two evaluators and considers the communicative effect of
the speaker’s linguistic production on the receptor and, therefore, comes close to the
main objective of the process of language acquisition, namely interpersonal
communication. Our evaluation system consisted of two criteria which measure
different aspects of written production (Lasagabaster and Doiz, 2003: 142-143):
(1) Content (30 points): this category considers the development and
comprehension of the topic as well as the adequacy of the content.
(2) Organization (20 points): several factors are considered here, namely the
organization of ideas, the structure and cohesion of paragraphs and the
17
clarity of exposition of the main and secondary ideas.
The results for each of the criteria were summed, the maximum score being 50. The
final score was the average of the total points assigned by each of two independent
evaluators. The inter-rater correlation (Pearson correlation coefficient) for the written
content subscore was 0.82; the organization subscore 0.89; and the total score 0.90
(for the oral data: 0.79, 0.81, 0.86). It was decided to include only two holistic
measures, since some authors have questioned the reliability and informativeness of
the holistic rating of compositions (for discussion, see Torras et al., 2006: 157ff.).
In the context of the quantitative approach, competence was measured in terms
of oral and written fluency, lexical and syntactic complexity, and morphosyntactic
errors. Following Wolfe-Quintero, Inagaki and Kim (1998), fluency was examined in
terms of words per T-unit, which is defined as one main clause and all of the
dependent modifying clauses (Ellis and Barkhuizen, 2005). We should mention that
words/T-unit is often also used as a complexity measure. Syntactic complexity was
examined in both languages using the clauses per T-unit complexity ratio. Lexical
complexity was examined using Guiraud’s Index of Lexical Richness: word types
divided by the square root of the word tokens. Accuracy was examined by counting
18
the number of misspellings (excluding ‘mechanical errors’ such as punctuation errors)
and the number of morphosyntactic errors per T-unit. Finally, oral fluency was
examined by means of pruned syllables per minute (see e.g. Gavin, 2014).
Language experience essays
Student perspectives occupy a central position in social constructivist approaches to
education (e.g. Brooks and Brooks, 2000; Larochelle et al., 2009) as well as in the
advocacy of autonomy in the classroom (e.g. Cotterall and Crabbe, 2008; Little,
2007; Ushioda, 2009, 2011), but individualized approaches to age research are still
scarce. Thus, in order to give a better account of the interaction of AO and other
(often hidden) variables such as motivation, attitudes and beliefs, we used language
experience essays, which we hoped would elicit (a) the participants’ reflections on
their experience of multiple FL learning at the beginning and at the end of secondary
school; (b) the participants’ affect in respect of foreign languages, and English in
particular; and (c) participants’ beliefs about the age factor (rationale of
complementarity, see research question 3). The use of these essays was based on the
19
idea that, on the one hand, learners’ beliefs are – consciously or unconsciously –
gleaned from past experiences; and that, on the other, learners’ beliefs have an
influential role in respect of learning outcomes (see e.g. Gregersen and MacIntyre,
2014). We provided loose guidelines for the writing. No specific length was set;
students wrote between 203 and 475 words.
Motivation questionnaire
On the basis of the data from the first qualitative phase, including the essays, we
constructed a more structured motivation questionnaire with 28 closed-ended and one
open-ended item, formulated in Standard German, which was administered to the
same 200 students twice, at the beginning and at the end of secondary school
(rationale of development, see research questions 1 and 2). The qualitative analysis of
the language experience essays was conducted in three stages. The first stage
involved separately reading through the essays for each student several times, getting
a general understanding of issues covered and taking note of interesting features.
Starting from the second reading, the essays were analyzed independently for
emerging categories. 15 categories emerged as significant relative to target language
20
development and age-related differences. Finally, after the saturation of categories,
some were merged with others, resulting in eight final categories:
1. Future L2 self-states
2. Present L2 self-states
3. FL learning anxiety
4. Linguistic self-confidence
5. Attitudes towards FLs in general
6. Attitudes towards the learning situation
7. Cultural interest and media usage
8. Parental encouragement
Future L2 self-states encompass learners’ ‘experiencing’ themselves in future states,
their strongly valued future possible selves that included the FL, such as the wish to
become similar to native speakers of English, and also the usefulness of the FL skills
to be learned in the future and the incentive value of success, i.e. the value of
potential outcomes and rewards, external or internal. This included a desired
21
(imagined) L2 community that offers possibilities for an enhanced range of identity
options in the future (see e.g. Norton, 2014).
According to Dörnyei (2009: 11) a person’s present L2 self has traditionally been
seen as “the summary of the individual’s self-knowledge related to how the person
views themselves at present” and is assumed to also concern information derived
from the individual’s past experiences (Markus and Nurius, 1986). Present L2 self-
states thus refer to the current attitudes learners displayed toward EFL and the FL
community and their reactions to a world in which English plays a predominant role,
as well as the extent to which the learners wanted to experience cross-cultural contact
involving English and travel to English-speaking countries. This dimension also
includes factors of external regulation leading to action in order to avoid bad grades
or to assuage a guilty conscience.
Making a distinction between present and future self-states is important for two
main reasons: on the one hand, the motivation literature emphasizes that motivated
behaviour occurs as the learners seek to reduce the gap between their ideal L2 self in
the future and their present self (e.g. Dörnyei, 2005, 2014). Measuring this gap can
thus shed light on early vs. late starters’ motivated behaviour. On the other hand,
reports from our language experience essays highlighted the fuzziness of the ideal L2
22
self/ought-to L2 self binary in the L2 Motivational Self System proposed by Dörnyei
(2005) as well as the integrativeness/instrumentality binary in Gardner’s Socio-
Educational Model of Language Learning (e.g. Gardner, 1985; Gardner and Lambert,
1959) (see Pfenninger and Singleton, in prep.). For instance, it turned out that
internalized instrumental motives, such as perceived benefits and usefulness of
English in a globalized world, can be part of the students’ ideal L2 self.
FL anxiety refers to “the worry and negative emotional reaction aroused when
learning or using a second language” (MacIntyre, 1999: 27). Since it has been
recommended (e.g. Dewaele and MacIntyre, 2014) that researchers examine both
positive and negative emotions in the same study, owing to the absence of anxiety
being ambiguous and thus difficult to interpret, we added linguistic confidence to
assess positive emotions. This dimension refers to the belief of learners that they are
capable of engaging in social interactions in the L2 and is often said to develop, on
the one hand, as a consequence of frequency of (prior) contact and quality (or
pleasantness) of contact with the L2 and members of the L2 group (e.g. Sampasivam
and Clément, 2014), or, on the other hand, as a precursor to contact when feelings of
confidence motivate learners to seek such contact (see e.g. Kormos and Csizér, 2008).
23
Attitudes towards FLs is concerned with FL learning in general and includes FLs
other than English (e.g. French). In order to give a full account of the role of FL
learning experiences, it was decided to include and adapt a category on attitudes
toward the learning situation, which covers the immediate learning situation
important to any study of L2 motivation in a classroom context (syllabus, teacher,
class atmosphere, etc.), as well as the learners’ sense that their behaviors are self-
determined even thought they might be influenced by external sources.
Students’ particular interest in English-speaking cultures would also have been
gauged by questions on cultural interest and media usage, relating to the appreciation
of cultural products as, for instance, delivered by the media.
Finally, we added one more dimension, parental encouragement, which refers to
the extent to which parents encourage their children to study English (Kormos and
Csizér, 2008). On the one hand, this dimension relates to previous findings in the
literature that parents can influence their children’s attitudes and motivation in subtle
and sometimes unconscious ways through their own attitudes to FLs or FL learning,
even without actively involving themselves in their children’s learning (see
Mihaljevic Djigunovic, 2012; Nikolov, 1999). In addition, we wanted to make
24
reference to the fact that parents frequently demand the inclusion of a FL in primary
school curricula (Kubanek-German, 1998).
Each category was allotted between two and eight items, giving a total of 28
items. Table 2 shows the Cronbach’s alpha reliability coefficients for the three multi-
item scales of the present study. All of the reliability coefficients are above the
recommended .70 threshold.
Table 2. Information about the multi-item scales.
Variables No. of
items
Cronbach’s
alpha
Sample item
Future L2 self-
states
8 .79 Whenever I think of the
future, I imagine myself as
someone who is able to
speak English.
Present L2 self-
states
7 .75 As a language, I don’t like
English.
FL learning
anxiety
2 .71 I get nervous when I speak
English in my English class.
Linguistic self-
confidence
2 .74 I am successful at learning
English.
Attitudes 2 .81 I like learning foreign
25
towards FLs languages in general.
Attitudes
towards the
learning
situation
2 .82 I usually look forward to
English classes.
Cultural interest 3 .84 I enjoy English language
movies and programs.
Parental
encouragement
2 .86 My parents encourage me to
study English.
A five-point Likert scale was used for all categories, to provide enough possibilities
(whilst avoiding confusion with the Swiss grading system, which scores 1-6). Some
of these questions were adapted for the Swiss school context, a third of them were
made negative, and the resultant list was translated into German and randomized.
Attention was paid to ensure that the questions were not beyond the grasp of the 13–
14 age groups at Time 1. The questionnaire was pilot-tested with 50 participants in
2008 (see Pfenninger and Singleton, in prep). This led to the deletion of some items
and the reformulation of others. Finally, in the open-ended question, the ECLs were
asked about the main differences between EFL in primary school and EFL in
26
secondary school and how they experienced the transition from primary to secondary
school with respect to English.
Modeling “learner-in-context”
The best ways to deal with a person-in-context relational view of age and motivation
are to employ multilevel models (Baayen, Davidson and Bates, 2008; Jaeger, 2008),
which are ideal for a potentially generalizable study of age effects and motivation,
given the availability of both individual-level and aggregated contextual-level data
with a sufficiently large number of groups. These models take into account, for
instance, that students within a classroom (and school) might be more similar to each
other than to students in other classrooms (and schools) by including random
intercepts. Multilevel models can also be used for assessing the impact of context-
varying factors on individual difference variables, and they take account of the fact
that different participants and/or classes and/or different items may vary with regard
to how sensitive they are to the manipulation at hand by including school-specific,
subject-speci c and item-specific slopes for the xed effect AO. They provide us withfi fi
a way to empirically measure and analyze contextual motivational factors, which are
27
often only implicitly reflected in the individual’s self-reported attitudes and
cognitions.
Table 3 displays the learner-level and class-level variables that we selected in
our model, where we controlled for the clustering of learners within particular classes
within particular schools:
Table 3. Student, class and school level variables.
Predictors (fixed effects)
Learner-level variables
•AO
•Time
•Motivation (8 motivational dimensions)
•Prior knowledge (scores at Time 1)
•Gender
Class-level variables
•Class size
Intercepts
•School (Level 3)
•Class (Level 2)
•Subject (Level 1)
28
Slopes
•Subjects across time
•School-specific, subject-speci c and item-specific slopes for the xedfi fi
effect AO
•Gender across classes and schools: Variation in FEMALE slopes
•Class size across schools
As Table 3 shows, we had five learner-level variables and one class-level variable.
We ran three multilevel analyses:
1. MLM 2-level analysis (class, school) examining impact of AO on L2
proficiency and motivation at Time 1 and Time 2; we allowed the effects of AO,
gender and class size on L2 achievement to vary across classes and/or schools.
2. MLM 2-level analysis (class, school) examining impact of motivation on
L2 proficiency at Time 1 and Time 2.
3. MLM 4-level (time, learner, class, school) examining individual growth
curves for L2 proficiency and motivation over two waves.
29
In 1 and 2 we wanted to see how much difference there was within a class and within
a school, i.e. whether all classes and all schools had the same relationships or whether
there was variability in the effect of the fixed variables (AO, gender, class size, time,
motivation) on learners’ L2 achievement. As the MLM in 3 shows, longitudinal data
can also be conceptualized as a hierarchy, where we have different observations
nested within people. The outcome and the occasions (time) were Level 1 variables,
the learner characteristics were Level 2 variables, class characteristics were at Level 3
and school characteristics at Level 4. Thus, in order to measure growth and
development over the years, we fitted 2-level linear growth models to each set of
longitudinal L2 proficiency scores. Note that when including continuous predictors
such as motivation in a mixed-effect model, it is often useful to center each predictor
around its mean value (see e.g. Cunnings, 2012: 376). This involves subtracting from
each individual value of a predictor the predictor’s overall mean, and is done to help
reduce collinearity within the model (e.g. between main effects and interactions).
Visual inspection of residual plots did not reveal any obvious deviations from
homoscedasticity or normality. P-values were obtained by likelihood ratio tests of the
full model with the effect in question against the model without the effect in question.
All models reported were fitted using Laplace estimation with the R software (R
30
Development Core Team, 2014) and lme4 (Bates, Maechler and Bolker, 2014). Also,
all models were rst evaluated with likelihood ratio tests (test model vs. null model fi
with only the control variables). If the full model vs. null model comparison reached
signi cance, we present fip-values based on likelihood ratio tests. Given the lack of
degrees of freedom with mixed models, we refrain from reporting df.
Results of the quantitative analysis
Research question 1
In accordance with our research questions (1)-(2), we will examine the impact of AO
and motivation on L2 achievement at both data collection times, and follow this with
a discussion of the influence of AO and time on motivation. The participants’
performance across all skills tested is shown in Table 4:
Table 4. Descriptive statistics (means and standard deviations).
TIME 1 TIME 2
ECL1
(n=100) LCL1
(n=100
)
ECL2
(n=100
)
LCL2
(n=100)
1 Listening
comprehension n.a. n.a. 12.61
(3.17) 12.08
(3.49)
2 Productive n.a. n.a. 25.46 25.11
31
vocabulary (7.47) (7.71)
3 Receptive
vocabulary 26.36
(8.59) 17.47
(8.05) 50.08
(7.14) 49.4
(7.54)
4 Written content 19.14
(2.61) 19.05
(2.19) 27.23
(1.95) 27.10
(2.01)
5 Written
organization 10.52
(1.99) 10.42
(2.05) 16.67
(2.96) 16.90
(2.45)
6 Written lexical
richness 4.92
(1.30) 4.17
(0.78) 7.57
(0.80) 7.73
(0.77)
7 Written fluency 10.88
(3.63) 10.78
(3.22) 14.91
(2.97) 14.15
(4.08)
8 Written
complexity 1.43
(0.39) 1.45
(0.31) 1.69
(0.61) 1.72
(0.46)
9 Written
accuracy 2.07
(0.63) 1.77
(0.58) 0.61
(0.44) 0.62
(0.56)
1
0Oral lexical
richness 4.01
(1.85) 3.22
(1.28) 5.55
(1.43) 5.63
(1.28)
11 Oral fluency 60.95
(16.55) 57.79
(8.17) 124.80
(12.78) 122.48
(12.96)
1
2Oral
complexity 1.30
(0.61) 1.34
(0.41) 1.57
(0.55) 1.61
(0.50)
1
3Oral
accuracy 3.46
(1.67) 2.79
(1.72) 1.20
(1.25) 1.30
(1.40)
1
4Grammaticalit
y
judgments
24.2
(3.78) 23.45
(3.41) 41.93
(3.31) 42.95
(2.79)
As can be seen in Table 4 and Table 5 below, the effect of AO is strong and
significant for the following dimensions at the beginning of secondary school:
receptive vocabulary and written lexical richness, for which an earlier AO were more
32
advantageous, and oral and written accuracy, where the late starters outperformed the
earlier starters:
Table 5. Multilevel regression analyses for scores as dependent variable at Time 1
(fixed effect estimates for AO).Fixed effect: AO
Estimate tMain
effect p
Receptive vocabulary -11.41 ± 1.32 -8.62 <.0001**
Written content -0.40 ± 0.43 -0.95 .255
Written organization -0.23 ± 0.35 -0.66 .477
Written lexical
richness -0.79 ± 0.22 -3.55 .001**
Written fluency -0.81 ± 0.50 -1.61 .062
Written complexity 0.01 ± 0.07 0.16 .845
Written accuracy -0.43 ± 0.10 -4.16 <.001**
Oral fluency -5.71 ± 8.80 -0.65 .474
Oral complexity -0.01 ± 0.34 0.03 .969
Oral accuracy -0.62 ± 0.29 -2.10 .030*
GJT -1.02 ± 0.87 -1.17 .210
At Time 2, there were no longer any links between the learners’ AO and their FL
achievement except for the significantly better grammaticality judgment results of the
late starters (see Table 6):
Table 6. Multilevel regression analyses for scores as dependent variable at Time 2
(fixed effect estimates for AO). Fixed effect: AO
33
Estimate tMain effect p
Listening -0.15 ± 1.09 -0.14 .874
Productive vocabulary 0.87 ± 2.78 0.31 .730
Receptive vocabulary -0.79 ± 1.50 -0.53 .603
Written content 0.07 ± 0.26 0.36 .707
Written organization 0.60 ± 0.62 0.96 .423
Written lexical richness 0.21 ± 0.12 1.80 .603
Written fluency -0.39 ± 0.54 -0.72 .327
Written complexity 0.05 ± 0.12 0.42 .625
Written accuracy -0.02 ± 0.07 -0.31 .749
Oral fluency -0.02 ± 0.07 -0.31 .972
Oral complexity 0.02 ± 0.28 0.83 .910
Written accuracy -0.02 ± 0.07 -0.31 .749
Oral accuracy 0.18 ± 0.20 0.90 .352
GJT 1.49 ± 0.55 2.73 .014*
This means that the late starters were able to make more progress within a shorter
period of time, i.e. there is a clear difference in rate of EFL learning in favor of the
late starters.
With respect to motivation, the two groups differed from each other at Time 1 in
terms of the strength of their future vision of themselves as competent L2 users, with
the late starters having significantly higher values, as well as in terms of their present
L2 self-states, which were stronger for the early starters – although the latter result
was only marginally significant. Table 7 presents the values for each motivational
dimension (descriptive statistics), while Table 8 shows the results of the multilevel
model with AO as the main predictor of motivation at Time 1:
34
Table 7. Descriptive statistics for motivation (means and standard deviations).
TIME 1 TIME 2
ECL1
(n=100
)
LCL1
(n=100
)
ECL2
(n=100
)
LCL2
(n=10
0)
1 Future selves 2.81
(0.76) 3.21
(0.90) 3.87
(0.70) 3.71
(0.63)
2 Present selves 3.27
(1.03) 2.75
(0.76) 3.39
(0.63) 3.42
(0.70)
3 FL learning
anxiety 2.94
(1.00) 2.31
(0.82) 2.07
(0.84) 2.11
(1.04)
4 Linguistic self-
confidence 2.99
(1.13) 3.06
(1.18) 3.10
(1.24) 3.05
(1.17)
5 Attitudes
towards FLs 1.98
(0.95) 2.51
(1.10) 3.03
(1.18) 3.18
(1.15)
6 Attitudes
towards the
learning
situation
2.43
(0.90) 2.97
(1.18) 3.36
(0.99) 3.40
(0.95)
7 Cultural
interest and
media
3.56
(1.00) 3.67
(0.91) 4.01
(0.71) 4.04
(0.69)
8 Parental
encouragement 2.78
(1.04) 3.00
(1.06) 3.57
(0.80) 3.47
(0.82)
Table 8. Multilevel regression analyses for motivation as dependent variable at Time
1 (fixed effect estimates for AO).
Fixed effect: AO
Estimate tMain
effect p
Future selves 0.32 ± 0.15 2.21 .030*
Present selves -0.52 ± 0.26 -2.02 .052*
Anxiety -0.52 ± 0.14 -3.68 <.001**
35
Confidence 0.08 ± 1.19 0.46 .645
Attitudes to FLs 0.54 ± 0.15 3.69 <.001**
Attitudes to
learning
Situation
0.57 ± 2.26 2.24 .027*
Culture and
media 0.11 ± 0.13 0.81 .413
Parental
encouragement 0.20 ± 0.22 0.22 .342
Note: “n.s.” indicates non significant; “n.a.” = non applicable.
Two observations are interesting with respect to the learners’ present and future self-
states. First, while the relationship between AO and future and present self
perceptions was the same across the five schools, there was significant between-class
and between-school variation concerning both these dimensions, as Figures 1 and 2
demonstrate for future self perceptions (although the results in Figure 2 are only
marginally significant):
36
1 2 3 4 5 6 7 8 9 10 11 12
12345
Classes
Motivation scores
Figure 1. Variation across classes for future L2 self-states at Time 1 (variance=0.06,
SD=0.25, p=.013*).
37
12345
12345
Schools
Motivation scores
Figure 2. Variation across schools for future L2 self-states at Time 1 (variance=0.03,
SD=0.16, p=.051*).
Classes and schools had a significant impact on students’ perceptions and
orientations. Also, whereas present self-states did not have the same impact on the
scores at either Time 1 or Time 2, future self-states had a large and significant effect
at both data collection times (see Tables 10 and 11 in the Appendix).
38
The LCLs were also less anxious than the ECLs at Time 1, and they had more
positive attitudes towards FLs and the learning situation (see Table 4 above). In fact,
the ECLs had extremely unfavorable attitudes towards FLs in general when they
began secondary school (mean value of 1.89 on a 5-point scale at Time 1). It has to be
pointed out, however, that anxiety, confidence, and attitudes to FLs did not impact on
the scores greatly at either measurement time (see Pfenninger and Singleton, in prep.
for a discussion of these findings). By contrast, attitudes to the learning situation had
a particularly marked impact after six years, i.e., after the classes’ structures had had
time to develop (see Tables 12 and 13 in the Appendix). Finally, parental
encouragement had a significant impact on proficiency at Time 1 but not at Time 2,
irrespective of AO (see Tables 14 and 15 in the Appendix). This is interesting insofar
as neither ECLs nor LCLs thought that their parents had had a particularly active,
encouraging role in respect of their L2 learning (see the values around 3.5 on a 5-
point scale for dimension 10 in Table 4 above).
Research question 2
With respect to motivation as a dependent variable (see research question 2), the
results did not show a decline in positive attitudes as students moved up the school.
39
Quite to the contrary, almost all orientations received higher values at Time 2, e.g.
future L2 self-states (see Figure 3; for all dimensions see Table 16 in the Appendix).
In addition, the two age groups showed a similar growth from Time 1 to Time 2 (see
Table 9) – except in regard to anxiety and attitudes to FLs, where the ECLs advanced
significantly more:
40
1.0 1.2 1.4 1.6 1.8 2.0
12345
Time
Motivation scores
AO groups
ECL LCL
Figure 3. Single-level regression of future L2 selves over time across the 12 classes
Table 9. Multilevel regression analyses for growth of the two age groups (fixed effect
estimates). Fixed effect: AO
Estimate tMain
41
effect p
Future selves 0.12 ± 0.18 0.67 .467
Present selves -0.24 ± 0.24 -1.00 .285
Anxiety -0.32 ± 0.12 -2.67 .019*
Confidence -0.03 ± 0.13 -0.24 .892
Attitudes to FLs 0.34 ± 0.13 2.55 .015*
Attitudes to
learning
Situation
0.21 ± 0.15 1.42 .144
Culture and
media 0.09 ± 0.11 0.86 .438
Parental
encouragement 0.05 ± 0.12 0.42 .647
Note. “n.a.” = non applicable
At Time 2, there were no longer any differences between the two age groups (Table
17 in the Appendix).
Not surprisingly, motivation varied across the 12 classes and the five schools.
Figure 4, for instance, shows evidence of the relationship between future L2 self-
states and receptive vocabulary being different:
42
12345
10 20 30 40
Motivation scores T1
Receptive vocabulary scores T1
AO groups
ECL LCL
Figure 4. Single-level regression of future L2 selves on receptive vocabulary at Time
1 across the 12 classes
The intercepts are very different (some classes have a higher intercept than other
classes) and the slopes are not the same, i.e. they are not exactly parallel. We can also
43
see a different pattern that emerges for the two AO groups: for the dotted lines (i.e.
the early starters) intercepts tend to be higher than for the long-dash lines (i.e. the late
starters), reflecting the early starters’ better scores on this test at Time 1 (see Tables 4
and 6 above), but the effect of this motivational dimension on receptive vocabulary
seems to be the same for both groups (the slopes were equally strong and weak
respectively). The differences in motivation slopes are thus not attributable to AO but
rather to characteristics of the clusters at the level of sampling. While there was
hardly any effect of gender on motivation or learner outcomes, we found a strong
negative effect for class size: as the number of students within a class increased, the
L2 performance (see e.g. receptive vocabulary in Figure 5) and particularly
motivation (see e.g. future L2 selves in Figure 6) tended to decrease at both data
collection times:
44
10 12 14 15 16 17 18 19 21
30 35 40 45 50 55 60
Number of students
Receptive vocabulary scores T2
Figure 5. Effects of class size on receptive vocabulary at Time 2 (b=-0.84, SE=0.23,
t=-3.66, p=0.0006**).
45
10 12 14 15 16 17 18 19 21
1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Number of students
Motivation scores T2
Figure 6. Effects of class size on future L2 selves at Time 2 (b=-0.08, SE=0.02, t=-
3.25, p=0.003*).
About 50% of the written measures were affected by class size, notably listening
comprehension, receptive vocabulary, spoken and written content, spoken and written
46
organization, written accuracy, and grammaticality judgments. Class size also had a
significant effect on all motivational dimensions – except for attitudes to FLs (at
Time 1 and 2), culture and media (at Time 1) and parental encouragement (at Time 1
and 2).
Research question 3
The results not only revealed variability in motivation effects across subjects, classes
and schools, but also significant variability in age effects across the five schools (see
research question 3). For instance, as Figure 7 shows, one of the four schools – the
only school in a suburban context – tended to have weaker slopes than the others
across all measures (here for receptive vocabulary at Time 1), which means there
were hardly any age-related differences found in this school context:
47
early late
10 20 30 40
AO groups
Receptive vocabulary scores T1
Schools
Figure 7. Single-level regression of AO on receptive vocabulary at Time 1 across the
five schools (variance=0.06, SD=0.24, p<001**)
48
This indicates that age-related differences are mediated by wider contextual factors.
Variation across classes could not be measured, since early and late starters were not
integrated in the same classes.
Results of the qualitative analysis
In order to be able to answer our last research question (4), regarding learners’ beliefs
about the age factor, we used the qualitative data drawn from a selection of the essays
written by the totality of 200 participants. Before we deal with the selection in
question, however, it may be interesting to delve into the responses to one of the
open-ended questions submitted by the totality of early English students, dealing with
the primary school experience vis-à-vis secondary. 78% of the responses in question
talked about the perception that English instruction in primary school had not focused
on explicit rule-learning, whereas in secondary school it very much had. 72% of the
responses concerned the perceived inefficiency of the way that early English was
taught. 56% of comments expressed criticism of the teacher’s choice of language of
instruction. 41% of students‘ answers to the question complained about the
experience of starting everything again from scratch in secondary school. Finally,
49
19% of students’ reactions offered some thoughts about the place of English versus
French in primary school.
We come now to the focal group, i.e., the 10 early high-achieving starters, the 10
early low-achieving starters, the 10 late high-achieving starters, and the 10 late low-
achieving starters. We concentrate here on retailing the learners’ perceptions with
regard to the age at which their instruction in EFL had begun.
The trend at Time 1 was for learners to be positive about the age that they
themselves had started learning English. The early high achievers came out fairly
uniformly at Time 1 with sentiments like the following:
(1) ‘The earlier the better’. We should learn foreign languages early because our
brain learns a foreign language faster when we’re children. (07_ELH3_M_GER)
At Time 1 the late high achievers tended, on the other hand, to support the pattern of
starting English later:
(2) I personally don’t think it’s good to begin learning too early ... so beginning
English at 12 or 13 I think is exactly right. (07_LLH10_F_GER)
50
The late low achievers also tended at Time 1 to support the pattern of starting English
later which they themselves had experienced:
(3) An 8-year-old child very probably still doesn’t understand grammar. He/she at
that time has other things in his/her head. (07_LLL4_M_GER)
The exception at Time 1 to the expression of satisfaction was the tenor of the
comments offered by the early low achievers, who were clearly less than charmed by
their encounter with English in primary school. At Time 2 the early high achievers
showed less unanimity than previously in regard to their assessment of the value of
early English. At Time 1 (see above), the views expressed by this group were
overwhelmingly favorable; when the learners in question were older the picture was
more mixed. Opinions supportive of early English were still in evidence; some more
nuanced, more skeptical views also appeared, however:
(4) I remember how in early years the learning was unconcentrated and slow. At
secondary level it progressed really fast. (12_ELH9_M_GER)
51
The early low achievers were, if anything, even more skeptical about early English at
Time 2 than they had been at Time 1.
(5) In my opinion the early ‘learning‘ of foreign languages ... isn‘t meaningful. First
really because they (the students) don‘t learn anything, but are only killing time and
get demotivated for foreign languages. Besides this, day by day they lose motivation
for school. (12_ELL1_F_GER)
Amongst the late-starting high-achievers at Time 2, as at Time 1, the
trend was for the late start in English that they had experienced to be approved:
(6) As a child I always envied my brother, who had English as early as the second class
of primary school. ... But looking back I don‘t see this advantage as so big any more.
Within half a year I had in the 2nd year of secondary school the same level of English
as my brother. (12_LLH6_M_GER)
52
The late low achievers at Time 2 remained as satisfied as they had been at Time 1
with late English, and as skeptical as they had been with regard to the wisdom of the
introduction of English at primary level. In sum, we learned from the language
experience essays that for the most part the late starters were content with and
positive about their late start, and that those who had been able to compare
themselves with early starters (e.g. younger siblings) did not find themselves at a
disadvantage from beginning English later. Amongst the early starters we found
differences between the high achievers and the low achievers. At Time 1 the mood
amongst the high-achieving early starters was very buoyant, many of the positive
opinions expressed, though, seeming to be based on ‘received wisdom’ about the
desirability of beginning English instruction early. At Time 2, views were mixed, a
number of high-achieving early starters referring to their disappointment with their
actual experience of early English. The pattern of perceptions voiced by the early low
achievers was mostly negative at both Time 1 and Time 2.
Discussion
53
In our study we first addressed the question about the main differences concerning L2
achievement in two different AO groups (research question 1). With respect to rate of
acquisition, it became obvious that the late starters were able to catch up very quickly
(i.e. within six months in secondary) with the performance of the early starters – who
had had five years more EFL instruction – with respect to a range of oral and written
measures, and that they were able to remain on a par with the early starters until the
end of obligatory schooling in Switzerland. The overall lack of effect of starting the
FL at an earlier age on FL achievement could be accounted for by reference to a
number of theoretical, affective and contextual factors. On a theoretical level the
long-term advantage conferred on most learners by an early start in a naturalistic
language learning context is not found in an FL learning context (see e.g. Muñoz,
2014b). With reference to possible reasons for the “kick start” of the LCLs at Time 1
and the general lack of age-related differences, the results indicated that for the LCLs,
motivation was more strongly goal- and future-focused at the first measurement,
while the motivation of the ECLs was predominantly influenced by (present and past)
cumulative experiential factors. Since future selves – but not present selves – had a
strong impact on the L2 achievement, the LCLs were possibly able to profit from
their orientations at Time 1. As outlined in the literature review above, the strong link
54
between a future time perspective and academic achievement is not new: students
who ascribe higher valence to goals in the distant future have been found to be more
persistent and obtain better academic results in the present (see e.g. Dörnyei, Muir
and Ibrahim, 2014). Since future selves contain an element of experiencing ourselves
in that future state, they involve a sense of agency, i.e. the belief that one is capable of
affecting outcomes in the future, based on past experiences and attributions for
success and failure. As mentioned above, agency is a vital characteristic of successful
learners and is central to appreciating their engagement, motivation, autonomy, and
self-regulatory behaviors (see e.g. Mercer, 2012). It is thus possible that due to their
past experiences in primary school the ECLs did not experience the requisite sense of
agency. Interestingly, the LCLs were able to keep their visions alive over time, as
they had similarly high values in this motivational dimension at Time 2. What is
more, the gap between present and future selves was the same for both AO groups at
Time 1. It is important to bear in mind, however, that there were no longer any
differences in terms of future self-states between the two AO groups at Time 2, and
for both groups, future self-representations were at that point stronger than present
self-states.
55
The expression of negative attitudes towards FLs and the learning
environment at Time 1 is a striking result for the early starters. From the qualitative
analysis it became clear that various factors seemed to contribute to the
disengagement of the early starters and might be responsible for the observed lack of
enthusiasm for engaging with English in school. These might include a lack of belief
in the efficacy of in-school learning environments among learners (see also Henry,
2014) and a relationship between not liking the teacher and not liking the subject (see
also Taylor, 2013). Resistance also appears to have arisen from a discrepancy
between the learners’ expectations of ‘good teaching’ and the pedagogical practices of
the teacher. It also seemed that the ECLs had to deal with a range of challenging
aspects of L2 learning at the beginning of secondary school, such as difficulty
adjusting to the new teaching style. This is also what Cenoz (2004) observed. She
found significant differences in favor of late starters when it came to the L2 learning
motivation of learners who were in the same school year (4th secondary) but who had
received different amounts of instruction. Cenoz hypothesized that this might have
been related to the differences in input and methodology between primary school and
secondary school. The ECLs’ responses also raise the question as to whether the skills
56
that are acquired in primary school are adequately measured and accredited in
secondary school.
The ECLs’ dissatisfaction with early English and the transition from EFL in
primary to EFL in secondary is problematic in several respects. Norton (2014), who
takes a poststructuralist view of motivation and resistance in a classroom, points out
that a student can be highly motivated and eager to learn English in general, but that
if the language practices of the classroom make a learner unhappy or dissatisfied, the
learner may resist participation in classroom activities, or become increasingly
disruptive. This position finds support from Ushioda (2014), who points out that
social-environmental conditions that undermine learners’ sense of competence will
generate forms of motivation that are less internalized, less integrated into the self or
aligned with its values, and more externally regulated by environmental influences,
pressures and controls. The reports in this study also confirm the influence of the
teacher that has been documented abundantly in the SLA literature (e.g. Noels et al.,
1999; Taylor, 2013; Ushioda, 2011). Lamb and Budiyanto (2013) explain that if the
teachers do not have any personal experience of Anglophone culture, English will be
taught and learned as a “values-free body of knowledge conveyed via official
textbooks” (26) and the students might become more oriented towards practice for
57
local and national exams. In a similar vein, anxiety can result from the classroom
situation (see e.g. Horwitz et al., 1986). For many students, the learning of English is
not an enjoyable activity in itself, but one which they have been required to persist at
for many years in primary school with negligible levels of success.
The fact that the LCLs were equally confident L2 speakers as the ECLs at
Time 1 despite their lesser contact with the L2 in a school context might be explained
in terms of the idea that linguistic confidence can also result from contact via foreign
media use, travel, and perceived importance of contact (see e.g. Clément et al., 1994;
Kormos and Csizér, 2008). At both data collection times we found very high values
for both AO groups in the area of cultural interest and media. Kormos and Csizér
(2008) observed that English language cultural products had a significant effect on
motivated behavior in secondary school pupils compared to adults for whom
“international posture” was a more important predictive variable (see also Tragant,
2006). This was also found in the data collected from 623 Hungarian students by
Kormos and Csizér (2008). Among the limited research on the facilitating effect of
computer-mediated communication (CMC) on L2 acquisition, findings suggest that
for beginning learners, the use of asynchronic CMC methods such as text chat can
58
allow learners to develop a sense of L2 confidence and alleviate anxiety (see Satar
and Ozdener, 2008).
As regards the question of development of motivation over the course of
secondary school (research question 2), our results show that learners do not
necessarily become more disenchanted with EFL over time. On the contrary, our
participants became increasingly more motivated in terms of a range of motivational
dimensions. In this respect our findings confirm those reported by, e.g., Dewaele and
MacIntyre (2014), who found a steady increase in FL enjoyment from pre-teens to
those in their thirties. However, we cannot say that more hours of instruction are
associated with more positive attitudes, as suggested, e.g., by Tragant and Muñoz
(2000), as there were no differences between the two AO groups with respect to
growth.
At the contextual level (see research question 3), our findings illustrate the
importance of school diversities – for example in school curricula, materials and
resources, teacher background and training – and their association with age-related
differences. The participants in this study came from different primary and secondary
school districts and neighborhoods and hence slightly different educational
backgrounds that emphasized different skills and values. It is thus not surprising that
59
we found variation across schools when it came to differences between early and late
starters. Previous studies have already demonstrated a strong link between socio-
economic status and achievement and motivation respectively (see e.g. Kormos and
Kiddle, 2013; Lamb, 2012). For instance, Muñoz (2008) argued that students from
different social backgrounds have access to different types of schools (state vs.
private) and to varying degrees of extracurricular exposure to the target language (e.g.
private tuition, learning resources, study abroad, etc.). While there were no students
from disadvantaged backgrounds in this study, the results nevertheless showed how
the school district can impact on students’ motivated behavior and, by extension,
mediate age-related differences: resources available and used in FL education are
dependent on schools, which might then influence learners’ intrinsic interest
indirectly (see e.g. Kormos and Kiddle, 2013), with the mediation of classroom
factors (Muñoz, 2008). Students who are highly motivated might thus be able to
make up for a later start. By the same logic, early starters who were in primary
schools with less than optimal learning conditions might not be able to profit from the
extended learning period, as they might have, for instance, significantly less favorable
future L2 self-state. It needs to be noted that motivated behavior and L2 performance
were also strongly influenced by class size in secondary school, which has also been
60
observed in numerous studies on willingness to communicate (see e.g. Cao and
Philip, 2006).
What could be considered a limitation of the current research might be the
relatively short instruction period of English instruction (five years) experienced by
our later beginners. Ideally, we should have liked to follow all our learners, or at least
some of them, through into higher education or whatever their next stage in life held
in store for them. Unfortunately, this was not possible for practical and logistical
reasons.
Conclusion
We can draw three general conclusions from the findings of our quantitative
multilevel analyses and the individual-learner qualitative data:
(1) While there were clear differences with respect to rate of acquisition in favor of
the late starters, we found no main effect for age at the end of mandatory school time,
which was also reflected in the qualitative data, e.g., in the reported comparisons that
late learners did with their younger siblings who had experienced early English – and
who failed, according to the reports, to perform better than the late starters.
61
(2) A strong future vision of L2 use and usefulness was a significant predictor of
success for both early and late starters – but only the latter displayed high values in
this motivational area at Time 1, which might have contributed to their kick-start at
the beginning of secondary school.
(3) The broader social and educational school context – i.e. the schools – played an
important role in attitude formation and in influencing students’ future L2 self-states,
which had a mediating effect on starting age.
(4) The quality of learners’ day-to-day experiences, shared histories and relations in
particular EFL classrooms represents an important microlevel that shaped students’
affective engagement with English and thus assumes particular importance for
discussions of motivation.
Our results thus run counter to the commonly held views that earlier starters show a
significant advantage over later starters due to their greater exposure, and that the
main gains of early FL learning lie in the development of positive attitudes and
motivation (e.g. Blondin et al., 1998; Edelenbos et al., 2007). Furthermore, positive
attitudes were not associated with biological age either, as younger learners were not
more motivated than older learners, i.e., motivation increased with time.
62
It seems that Ushioda’s (2013) observation holds true that “it is what happens (or
does not happen) in each individual classroom, as orchestrated by the teacher, that
will have a critical bearing on how students are motivated (or not) to invest effort in
learning English” (235). Since it is at a very localized level of students’ learning
experience that the real potential for engaging (or disengaging) their motivation may
lie, there is an increasing need for methods that obtain ecologically valid tests of age
effects in a classroom. The method described in the quantitative part of this paper,
multilevel modeling (MLM), turned out to be a convenient method, as it reduces
arbitrariness because it more closely reflects the influence of situations as they are
encountered in the students’ daily lives and thus achieves adequate estimates of
variances and therefore correct standard errors and correct inferences and (likelihood-
based) p-values. MLM thus highlights the growing methodological sophistication of
group researchers as they identify new ways to deal with the challenge of studying
individuals nested in groups (Forsyth, 2010). That is not to say that contextually-
grounded research approaches do not necessarily have to be qualitative anymore.
While MLM allows us to integrate contextual factors, context is defined as an
independent background variable that influences motivation, AO and proficiency, but
over which learners have no control (see Ushioda, 2009). The qualitative dimension
63
allows analysis to arrive at a “flavor” of learners’ perceptions and reactions which is
very often indispensable when it comes to constructing a true-to-life interpretation of
the quantitative data. In the ever-growing system of educational accountability it is
imperative that studies of age effects examine the way that schools and classes can
use climatic characteristics to influence students’ academic performance.
64
Appendix
Table 10. Fixed effect estimates for Future selves and Present selves at Time 1.
Fixed effect: Future selves
Estimate tMain
effect p
Receptive vocabulary 2.95 ± 0.54 5.45 <.001**
Written content 1.30 ± 0.25 5.29 <.001**
Written organization 1.27 ± 0.21 6.12 <.001**
Written lexical
richness 0.18 ± 0.12 1.51 .129
Written fluency 1.49 ± 0.30 4.91 <.001**
Written complexity 0.14 ± 0.04 3.84 <.001**
Written accuracy 0.39 ± 0.06 6.84 <.001**
Oral fluency 0.04 ± 8.80 -0.65 .938
Oral complexity 0.00 ± 0.03 0.11 .916
Oral accuracy 0.15 ± 0.20 1.76 <.001**
GJT -0.52 ± 0.41 -1.30 .208
Fixed effect: Present selves
Estimate tMain
effect p
Receptive vocabulary 1.95 ± 0.43 4.50 <.001*
Written content 0.32 ± 0.19 1.66 .151
Written organization 0.14 ± 0.16 0.87 .385
Written lexical
richness 0.15 ± 0.09 1.58 .150
Written fluency 0.20 ± 0.24 0.83 .477
Written complexity 0.06 ± 0.03 2.18 .035*
Written accuracy 0.01 ± 0.04 0.15 .946
Oral fluency 0.25 ± 0.43 0.57 .567
Oral complexity 0.02 ± 0.03 0.76 .448
Oral accuracy 0.11 ± 0.16 0.68 .540
GJT 0.06 ± 0.32 0.19 .843
65
Table 11. Fixed effect estimates for Future selves and Present selves at Time 2.
Fixed effect: Future selves
Estimate tMain
effect p
Listening -0.30 ± 0.41 -0.74 .476
Productive
vocabulary -0.21 ± 0.88 -0.24 .816
Receptive
vocabulary -0.09 ± 0.63 -0.14 .933
Written content 0.11 ± 0.23 0.50 <.001**
Written
organization 1.48 ± 0.33 4.47 <.001**
Written lexical
richness 0.58 ± 0.09 6.68 <.001**
Written fluency 2.04 ± 0.39 5.20 .001**
Written
complexity 0.32 ± 0.06 5.18 <.001**
Written accuracy -0.34 ± 0.06 -5.71 <.001**
Oral fluency -0.20 ± 0.83 -0.25 .783
Oral complexity 0.06 ± 0.04 1.86 .042*
Oral accuracy 0.14 ± 0.16 0.89 .374
GJT 2.00 ± 0.35 5.74 <.001**
Fixed effect: Present selves
Estimate tMain
effect p
Listening 0.05 ± 0.40 0.12 .896
Productive
vocabulary 0.33 ± 0.85 0.39 .700
Receptive 1.73 ± 0.61 2.83 .004*
66
vocabulary
Written content -0.21 ± 0.14 -1.53 .607
Written
organization 0.08 ± 0.36 0.25 .866
Written lexical
richness -0.13 ± 0.09 -1.48 .135
Written fluency -0.28 ± 0.41 -0.69 .464
Written
complexity 0.03 ± 0.07 0.45 .711
Written accuracy -0.00 ± 0.06 -0.01 .988
Oral fluency -1.21 ± 0.95 -1.23 .175
Oral complexity 0.02 ± 0.04 0.51 .626
Oral accuracy 0.02 ± 0.17 0.12 .913
GJT 0.12 ± 0.37 0.31 .810
Table 12. Fixed effect estimates for Attitudes to learning situation at Time 1.
Fixed effect: Attitudes to learning situation
Estimate tMain effect
p
Receptive
vocabulary 1.22 ± 0.39 3.14 .002*
Written
content -0.21 ±
0.15 -1.36 .271
Written
organizatio
n
0.09 ± 0.13 0.73 .519
Written
lexical
richness
0.09 ± 0.07 1.27 .188
Written
fluency 0.57 ± 0.19 2.98 .004*
Written
complexity -0.02 ±
0.02 -0.91 .345
Written -0.10 ± -2.73 .005*
67
accuracy 0.04
Oral
fluency 0.18 ± 0.33 0.54 .575
Oral
complexity -0.02 ±
0.02 -1.23 .220
Oral
accuracy -0.08 ±
0.12 -0.67 .509
GJT -0.24 ±
0.26 -0.95 .315
68
Table 13. Fixed effect estimates for Attitudes to learning situation at Time 2.
Fixed effect: Attitudes to learning situation
Estimate tMain effect
p
Listening -0.23 ± 0.25 -0.93 <.001**
Productive
vocabulary 0.25 ± 0.52 0.50 <.001**
Receptive
vocabulary 0.30 ± 0.38 0.80 <.001*
Written content -0.06 ± 0.22 -0.29 <.001**
Written
organization 0.02 ± 0.21 0.10 <.001**
Written lexical
richness -0.03 ± 0.09 -0.48 <.001**
Written fluency 0.45 ± 0.26 0.23 <.001**
Written
complexity 0.02 ± 0.04 0.52 <001**
Written accuracy 0.05 ± 0.04 1.36 <.001**
Oral fluency -0.70 ± 0.51 1.44 <.001**
Oral complexity -0.07 ± 0.02 -2.89 <.001**
Oral accuracy -0.02 ± 0.10 -0.23 <.001**
GJT 0.10 ± 0.22 0.43 <.001**
Table 14. Fixed effect estimates for Parental encouragement at Time 1.
Fixed effect: Parental encouragement
Estimate tMain effect p
Receptive
vocabulary 1.75 ± 0.37 4.77 <.001**
Written content 0.17 ± 0.17 1.01 <.001**
Written organization 0.24 ± 0.14 1.74 <.001**
Written lexical
richness -0.15 ± 0.08 -0.18 <.001**
Written fluency 0.22 ± 0.21 1.04 <.001**
Written complexity -0.03 ± 0.02 -1.26 <.001**
Written accuracy 0.03 ± 0.04 0.70 .001*
69
Oral fluency 0.47 ± 0.36 1.30 <.001**
Oral complexity 0.02 ± 0.02 1.02 .969
Oral accuracy -0.21 ± 0.13 -1.58 <.001**
GJT 0.22 ± 0.27 -0.80 <.001**
Table 15. Fixed effect estimates for Parental encouragement at Time 2.
Fixed effect: Parental encouragement
Estimate tMain
effect p
Listening -0.35 ± 0.29 -1.20 .212
Productive
vocabulary 0.62 ± 0.62 0.99 .319
Receptive
vocabulary 1.32 ± 0.45 2.96 .003*
Written content 0.26 ± 0.17 1.54 .114
Written
organization 0.30 ± 0.25 1.19 .236
Written lexical
richness 0.01 ± 0.07 .156 .823
Written fluency 0.12 ± 0.30 0.39 .717
Written
complexity 0.15 ± 0.04 3.28 <.001**
Written accuracy 0.01 ± 0.04 0.22 .824
Oral fluency -0.41 ± 0.60 -0.69 .446
Oral complexity -0.02 ± 0.03 -0.75 .443
Oral accuracy 0.24 ± 0.12 1.98 .049*
GJT -0.01 ± 0.26 -0.05 .879
70
Table 16. Multilevel regression analyses for development of motivation.
Fixed effect: Time
Estimate tMain
effect p
Future selves 0.78 ± 0.07 10.81 <.001**
Present selves 0.40 ± 0.07 5.56 <.001**
Anxiety -0.50 ± 0.09 -5.29 <.001**
Confidence 0.05 ± 0.11 0.44 .662
Attitudes to FLs 0.83 ± 0.11 7.81 <.001**
Attitudes to
learning
situation
0.68 ± 0.10 6.67 <.001**
Culture and
media 0.41 ± 0.08 4.97 <.001**
Parental
encouragement 0.63 ± 0.09 6.76 <.001**
Table 17. Multilevel regression analyses for motivation as dependent variable at
Time 2 (fixed effect estimates).
Fixed effect: AO
Estimate tMain
effect p
Future selves -0.02 ± 0.05 -0.47 .456
Present selves -0.01 ± 0.30 -0.04 .966
Anxiety -0.02 ± 0.16 -0.15 .896
Confidence 0.02 ± 0.18 0.11 .870
Attitudes to FLs 0.20 ± 0.29 0.67 .464
Attitudes to
learning
situation
-0.00 ± 0.16 -0.03 .851
Culture and
media -0.04 ± 0.16 0.26 .784
Parental
encouragement -0.08 ± 0.14 -0.64 .525
71
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