PERSONALIZED LEARNING RELIABILITY OF TELL ME MORE: A DYNAMIC

APPROACH

CONFIABILIDADE DE APRENDIZAGEM PERSONALIZADA DE TELL ME MORE:

UMA ABORDAGEM DINÂMICA

FIABILIDAD DE APRENDIZAJE PERSONALIZADO DE TELL ME MORE: UN

ENFOQUE DINÁMICO

Maria SHOBEIRY

ABSTRACT: This study investigated the personalized learning reliability of Tell Me More

(TMM) (i.e. the extent to which two hypothetical identical learners receive the same level of

instructional and learning support while using a courseware) within the dynamic framework of

Tetzlaff, Schmiedek, and Brod (2020), in which personalized learning is considered to be the

most reliable and effective when learners’ characteristics are dynamically assessed during the

learning procedure and the instructions are provided to them accordingly. The lessons,

workshops, and activities of TMM’s Dynamic mode were qualitatively analyzed and the results

revealed that in order for TMM to provide a reliable personalized learning, it should be

equipped with a placement test at the beginning of the course and a constant dynamic

assessment technology throughout the learning process. Relying on adaptive activities chosen

unsystematically by the learners themselves is not reliable in that most learners are neither

capable of professionally estimating their own level of language proficiency nor are they trained

to determine the required level of task difficulty for their activities. The results have

implications for courseware designers to consider placement tests and dynamic assessment

technology in their future designs to maximize the reliability of their personalized learning

programs.

KEYWORDS: Personalized learning reliability. Tell Me More. Dynamic assessment.

Placement test.

RESUMO: Este estudo investigou a confiabilidade de aprendizagem personalizada do Tell Me

More (TMM) (ou seja, a extensão em que dois alunos hipotéticos idênticos recebem o mesmo

nível de apoio instrucional e de aprendizagem ao usar um material didático) dentro da

estrutura dinâmica de Tetzlaff, Schmiedek e Brod (2020), em que a aprendizagem

personalizada é considerada a mais confiável e eficaz quando as características dos alunos

são avaliados dinamicamente durante o processo de aprendizagem e as instruções são

fornecidas a eles de acordo. As aulas, workshops e atividades do modo Dinâmico do TMM

foram analisadas qualitativamente e os resultados revelaram que para que o TMM proporcione

uma aprendizagem personalizada confiável, ele deve ser equipado com um teste de nivelamento

no início do curso e uma tecnologia de avaliação dinâmica constante ao longo do processo de

aprendizagem. Depender de atividades adaptativas escolhidas de forma não sistemática pelos

próprios alunos não é confiável, pois a maioria dos alunos não é capaz de estimar

PhD Candidate, Department of Applied Linguistics, University of Tehran, Tehran, Iran. ORCID:

https://orcid.org/0000-0002-2499-0366. E-mail: maria.shobeiry@ut.ac.ir

profissionalmente seu próprio nível de proficiência no idioma, nem são treinados para

determinar o nível necessário de dificuldade da tarefa para suas atividades. Os resultados têm

implicações para que os designers de material didático considerem os testes de colocação e a

tecnologia de avaliação dinâmica em seus projetos futuros para maximizar a confiabilidade de

seus programas de aprendizagem personalizados.

PALAVRAS-CHAVE: Confiabilidade de aprendizagem personalizada. Tell Me More.

Avaliação dinâmica. Teste de nivelamento.

RESUMEN: Este estudio investigó la confiabilidad del aprendizaje personalizado de Tell Me

More (TMM) (es decir, el grado en que dos estudiantes idénticos hipotéticos reciben el mismo

nivel de apoyo educativo y de aprendizaje mientras usan un material de curso) dentro del

marco dinámico de Tetzlaff, Schmiedek y Brod (2020) en el que se considera que el aprendizaje

personalizado es el más fiable y eficaz cuando las características de los alumnos se evalúan

dinámicamente durante el proceso de aprendizaje y se les proporcionan las instrucciones

correspondientes. Las lecciones, talleres y actividades del modo Dinámico de TMM se

analizaron cualitativamente y los resultados revelaron que para que TMM brinde un

aprendizaje personalizado confiable, debe estar equipado con una prueba de nivel al inicio del

curso y una tecnología de evaluación dinámica constante. durante todo el proceso de

aprendizaje. Depender de actividades adaptativas elegidas de forma no sistemática por los

propios alumnos no es fiable, ya que la mayoría de los alumnos no son capaces de estimar

profesionalmente su propio nivel de dominio del idioma ni están capacitados para determinar

el nivel requerido de dificultad de la tarea para sus actividades. Los resultados tienen

implicaciones para que los diseñadores de material educativo consideren las pruebas de

ubicación y la tecnología de evaluación dinámica en sus diseños futuros para maximizar la

confiabilidad de sus programas de aprendizaje personalizados.

PALABRAS CLAVE: Confiabilidad de aprendizaje personalizado. Tell Me More. Evaluación

dinâmica. Prueba de nivel.

Introduction

In the field of language teaching and learning, the use of technology and courseware has

started since 1960s. Appropriate integration of technology and pedagogy can support learning

effectively and engage learners in various ways since in the 21st century technology roots in

people' daily lives all over the globe (KENNING, 2007). Some courseware can provide

language learners with corrective feedback, proper instructional materials, authentic materials,

and cognitively and affectively engaging learning materials based on their algorithm (KRUSE

2004). Some language learning courseware can play the role of speaking partners, and some

can provide the chance of global learning all over the world through introducing suitable

speaking partners to each other via internet. These methods of learning are motivational to

language learners due to the possibility of personalization they provide during the learning

practice (LEE, 2008).

Among various available courseware, this study is mainly concerned with Tell Me

More (TMM hereafter) in that this courseware is easily available to Iranian language learners

and many Iranian language schools use it as a supplementary learning software in their

programs.

TMM is a virtual language teaching software which is offered in English, Spanish,

French, Italian, German, Dutch, Chinese, Japanese, and Arabic with 2000 hours of instructional

materials for each language. TMM could be considered as a supplementary learning program

to the main four skills of writing, reading, speaking, and listening through offering multimedia

videos, digitized sounds, and state-of-the-art speech recognition technology for teaching

pronunciation.

An intriguing functionality of TMM (version 10) is its dynamic mode which is defined

as the adjustability of the software according to the users' needs, interests, educational goals,

and personal profiles. The adaptation takes place during the language learning activities by

constantly analyzing the users' responses to the questions and accordingly adjusting the next

activities with the user's needs. This is a form of personalization in language learning which

allows learners to progress at their own pace of learning without feeling any pressure to keep

up with the other learners (KUKULSKA-HULME, 2016; TOMLINSON; MASUHARA,

2018). Through providing personally suitable teaching materials for language learners and

providing feedback TMM can turn traditional dependent learners into autonomous language

students (BUNTING, 2010).

There are various types of activities in TMM workshops to provide a wide range of

learning opportunities for the users. The most tangible activities in TMM comprise the

following:

 Interactive dialogue;

 Sentence pronunciation;

 Word pronunciation;

 Phonetic exercises;

 Word association;

 Word search;

 Fill-in the blanks;

 Words and functions;

 Words and topics;

 Grammar practice;

 Mystery phrase;

 Crossword puzzle;

 Word order;

 Dictation;

 Text transformation;

 Written expression;

 Video and questions.

The extent of TMM (version 10) courses are very vast in that each course contains 1200

exercises which are categorized in 35 types of activities. The main features of educational

procedures on TMM include:

 Interactive conversations with 15000 words and 8000-word glossary;

 Grammar and 700 conjugated words using simple animated explanations;

 A detailed diary of learners' progress;

 Personalized learning journey through adjustable activities.

Strengths of the TMM courseware have been counted by Bunting (2010) as:

1. The operational system of the software is smooth and user-friendly specifically

concerning the video and sound components;

2. The various types of activities are inspiring and motivating to language learners;

3. The program works well on Windows and mobile phones both Android and iOS;

4. Switching among languages are easy in this program;

5. The program supports six languages including Dutch, English, French, German,

Spanish, and Italian;

6. Learners face a great deal of repetition of words during various activities;

7. The program works with both mouse and keyboard which makes it easier for

various users to enjoy the program;

8. The activities are very straight forward and instructions are available step-by step.

Abovementioned statements were some general descriptions about the main

characteristics of TMM program. In the following section some studies on various aspects of

TMM are reviewed to achieve a clearer picture of the role and effectiveness of this courseware

in the realm of language learning.

Review of the related literature

Despite the huge load of studies performed on various aspects of computer assisted

language learning in the literature, there is limited number of studies incorporating TMM.

Studies on TMM in the current literature could be categorized into two main groups: 1) the

research in which the main focus was on the perception of the users of TMM (e.g., HASHIM;

YUNUS, 2010; EPINOSA, 2013; UTHAYAKUMARAN; KASSIM, 2018); and 2) the studies

which investigated the effect of TMM on various aspects of learners' language proficiency

which are usually limited in scope (e.g., PEREZ, 2014; AYULISTYA ,2016).

The study of Hashim and Yunus (2010) is an example of surveying the users of TMM

about their perceptions of TMM effectiveness and usefulness in learning settings. In this study

the attitude of a number of ESL college lecturers in Malaysia toward the ease of use, usefulness,

and suitability of TMM was explored through performing several semi-structured interviews.

The results revealed a positive attitude of the Malaysian ESL teachers toward the ease of use,

usefulness, and suitability of TMM. Nonetheless, they found that TMM is not perceived to be

a suitable courseware for teaching and learning of writing. Another study in this realm is a

mixed-method design research conducted by Uthayakumaran & Kassim (2018) on students'

perception of the effectiveness of TMM as a pronunciation learning software. In this study the

main focus was on vocabulary acquisition and pronunciation development of 28 university

students. The researchers also demonstrated a mixed perception of the participants about the

effectiveness of using TMM as a pronunciation learning software. Similar to the previous

studies, the study of Epinosa (2013) illustrated a positive attitude of the group of university

teachers in Spain toward utilizing TMM who employed it for a six-month period of instruction.

The results of this study revealed a moderate to low capacity of the program in improving

learners' communication skills.

Gyamfi and Sukseemuang (2017) studied the perceptions, practices, and achievement

of 340 EFL learners who used TMM as an instructional tool through. They employed

questionnaire and semi-structured focus group interview to collect data and demonstrated a

moderate level of participants' positive perception of TMM in learning English. Furthermore,

the analysis of the participants' scores revealed an improvement in learners at elementary and

advanced levels of language proficiency, while, strangely, intermediate learners showed a drop

in their achievement after using TMM. In another study Gyamfi and Sukseemuang (2017)

investigated factors affecting EFL learners' use of TMM and demonstrated a positive attitude

of the EFL learners toward using TMM in that TMM was reported by the learners to be

remarkably motivational and positively influential in their pre-communication skills

improvement.

In the realm of studies that explored the effectiveness of TMM in language achievement

the study of Ayulistya (2016) is of importance in that she investigated the effect of TMM on 20

high school students' pronunciation improvement and also explored their attitude toward using

it. Her results indicated a significant effect of TMM on improving the learners' pronunciation

with displaying 63% of the participants having held a positive attitude toward employing TMM

as a teaching service. The interesting point in the literature on TMM is that this courseware is

found to be effective in improving speaking and listening skills of its users; however, reading

and writing skills are not reported to be affected by this courseware as much as expected. This

is demonstrated in the study of Perez (2014) on the effectiveness of TMM in communication

skills of 108 paramedical and non-paramedical students. The results revealed a high level of

effectiveness of TMM in improving the listening and speaking skills of the participants; while

TMM was found to be less effective in developing their writing and reading skills.

What is missing from the literature on TMM is the lack of studies on the effectiveness

of personalization and the reliability of personalized learning in TMM as is claimed by its

producers. There are three modes for navigation in TMM including: Free-to-Roam, Guided,

and Dynamic in which language learners can select the type of activities and the level of

difficulty of the tasks they want to perform. The Dynamic mode of the program is the option

that provides personalized learning through modifying users' choices according to their

previous results in other activities and their interests, needs, objectives in their personal profiles.

Personalized learning is an educational approach within the theoretical framework of

Gardner's (1983) multiple intelligence aiming at customizing learning procedures according to

each learner's strengths, needs, objectives, skills, and interests. In this approach each student is

provided with a learning plan which is mainly based on what they know and how they learn

best (LEFEVRE; JEAN-DAUBIAS; GUIN; 2009). Despite the promising results expected from

this approach, applying personalization is extremely difficult in traditional classroom

environments. Modifying activities according to each learner's needs and goals could be

overwhelming for any teacher; therefore, personalization is more practical in private tutoring

sessions or virtual E-learning settings (THIYAGARAJAN, 2020). In setting up a personalized

educational environment, providing appropriate instructional methods and suitable teaching

materials occurs through employing dynamic assessment and providing constructive feedback

(POLLARD; JAMES, 2004). Therefore, personalized education is about how learners learn

rather than what they learn (TOMLINSON, 2013).

In this study, the concept of dynamic approach to language learning is related to

noticing constant changes in language learners' abilities and reacting to these changes

accordingly during instructional procedures. This involves employing consistent dynamic

assessment during the instructional process in order to discover learners' new educational needs

and accordingly design suitable instructional plans throughout the teaching practice

(TETZLAFF; SCHMIEDEK; BROD, 2020). Dynamic assessment is an interactive assessment

in education which is based on the sociocultural theory of mind proposed by Vygotsky (1978).

It identifies traits, abilities, or characteristics that a student has already mastered (the Zone of

Actual Development) and determines the learner's abilities in performing a task with the help

and support of a more knowledgeable person (within the Zone of Proximal Development). In

other words, dynamic assessment determines the extent to which a learner needs to receive

educational support during the learning procedure to achieve an educational goal.

Tetzlaff et al. (2020) proposed three ways in which learners' dynamic changes take

place:

1. Change in response to an intervention even in the form of a short-term

fluctuation. For example, changes in attitude toward a topic or metacognitive

strategies used by learners;

2. Changes in response to the same instruction in the same learner in various times.

This means that the same person reacts to the same instruction differently from

time to time;

3. Changes in response to the same instruction among various learners in time;

meaning, various learners react to the same instruction differently and this

difference even varies from time to time according to the contextual features and

internal factors of the learners.

Considering these three main ways of constant changes in learners, only applying

continuous dynamic assessment at different learning timescales can determine the

appropriateness of the instructional design and suitability of the planned activities during the

personalized learning procedure (TETZLAFF et al., 2020). It is worth mentioning that

instruction in this paper is used as an umbrella term meaning any interaction between learning

and teaching agents that has direct or indirect consequence in the learning procedure.

Furthermore, “personalization” in this research is used as a synonymous with

“individualization,” meaning any adjustment of instructional practice is designed for a specific

learner; therefore, it should include specified forms of assessment and instruction for each

learner according to their activities and personal profile.

I define personalized learning reliability in this study as the degree to which two

hypothetical identical learners with the same level of language proficiency and personal

preferences will receive the same level of instruction and learning support from the courseware.

Therefore, considering the abovementioned characteristics of TMM and the claimed capacity

of the personalized learning functionality of it, this study is an attempt to answer to the

following research question:

 Is personalized learning in dynamic mode of TMM reliable from a dynamic

approach to personalized learning?

Method

Data

To evaluate the personalized learning reliability of TMM (version 10), the lessons,

activities, and workshops provided by the dynamic mode of TMM for three language learners

at elementary, intermediate, and advanced levels were qualitatively analyzed as the data for this

study.

Evaluation framework

The theoretical framework of Tetzlaff et al. (2020) is employed as the evaluation

framework for personalized learning effectiveness and reliability in this study. In this

framework, personalized learning is proposed to be the most reliable and effectual when

relevant characteristics of learners are measured repeatedly throughout the learning procedure

in a dynamic framework. This is the main outline of dynamic approach to personalized learning

which includes providing opportunities for instructional adaptation, setting appropriate learning

goals, and reacting to affective-motivational fluctuations of the learners.

According to Tetzlaff et al. (2020) reliable and effective personalization includes three

steps as follows:

Step 1—Initial assessment of learner characteristics which includes systematically

assessing learners' features that are related to a specific learning procedure in order to establish

a student profile at the outset of the course.

Step 2—Instructional design which fits learners' profiles the most in terms of their

educational needs and goals.

Step 3—Progress assessment which includes using task performance analysis and

embedded dynamic assessment to update the learners' profiles based on their constant

progression.

As is shown in Figure 1, in this framework the steps 2 and 3 are extremely

interconnected and support each other throughout the personalized learning procedure.

Figure1. Theoretical framework for personalized learning evaluation

Source: Tetzlaff et al., 2020

Data analysis and results

The profiles of three language learners are qualitatively analyzed within the framework

of Tetzlaff et al. (2020) to indicate the personalized learning reliability of TMM.

The first noticeable fact in evaluating the program is the lack of placement test at the

beginning step of the learning procedure. TMM provides learners with the option of making

personal profiles before starting the learning process in which learners can indicate their own

level of language proficiency and the level of task difficulty by checking a box enumerated

from 1 to 10+. Then the learners are guided to choose among the three modes of Free to roam,

Guided, and Dynamic. All the lessons and activities in any of these three modes will be matched

with the level of proficiency that the learner registered in at the beginning step; however, the

main problem with this type of personalization is that it completely relies on the learners'

unprofessional estimate of their own level of language proficiency and cannot be considered

reliable.

I start with the profile of a twelve-year-old female elementary language learner. Since

there is no placement test in TMM, she had to estimate her own level of language proficiency

to be able to continue with making a profile. This was an overwhelming task for a twelve-year

old beginning user of the courseware; thus, she was asked to take the Cambridge online

placement test for young learners to indicate her level of language proficiency. The results of

the Cambridge placement test showed that she was at A2 level of language proficiency

according to Common European Framework of Reference for Languages (CEFR). Another

challenge that a learner faces in using TMM is to select the level of task difficulty which is

leveled from 1 to 10+ (shown in figure 2). In this pathway, there is no assessment of any kind

or any form of direction to show how to estimate the appropriate level of difficulty for the

various users. Therefore, personalization, up to this point, is mainly based on unprofessional

estimations of the users without any systematic assessment of the users' educational needs or

goals.

Figure 2. The table of content difficulty for personalized adjustment in TMM

Source: Author’s archive

The next step is to select the objectives of learning and personalizing it according to

knowledge (shown in Figure 3) and according to skill (shown in Figure 4) through indicating

its level of difficulty. Again, here there is no systematic assessment for indicating the most

suitable level of difficulty in each skill for each learner. Learners unsystematically select the

level of difficulty of their tasks as part of their personalized learning procedure, which could be

negatively influential and demotivating to them if the tasks' level of difficulty does not match

their educational needs and goals (ELLIS, 2016; TOMLINSON, 2013b).

Figure 3. Selecting learning objectives and personalizing it in TMM according to knowledge

Source: Author’s archive

Figure 4. Selecting learning objectives and personalizing it in TMM according to skill

Source: Author’s archive

Furthermore, analyzing this learner's profile showed that when she selected a task's level

of difficulty much higher than her suitable language proficiency level, the reaction of the

program is to provide a task with a one or two levels lower than the level of the previous activity

while in some cases it was needed for the learner to continue with at least 5 or 6 levels below

the previous chosen task. This reveals the importance of dynamic assessment during

instructions in personalized learning programs. Since TMM is not equipped with a constant

dynamic assessment system, most of its activities neither match with the users' current level of

language proficiency nor do they fulfill the users' educational needs. Although it is claimed by

TMM producers that the Dynamic mode of the courseware defines activities and instructions

according to the learners' needs (Figure 5), in reality there is no systematic matching system in

TMM's Dynamic mode to ensure the reliability of the personalized learning of the program.

Figure 5. Dynamic mode of TMM

Source: Author’s archive

The second analysis is related to the profile of a 32-year-old man in the intermediate

level of language proficiency (B2) and the third profile was related to a 41-year-old female pre-

advanced user of TMM (C1). The noticeable point in analyzing the intermediate and advanced

profiles was that TMM considers learner's objective progress and task completion (shown in

Figure 6) as a determining factor for the level of success of the learning procedure. This is

obviously a big flaw. Without any systematic assessment and only by relying on completing

some tasks, which somehow could have taken place randomly, the level of language

achievement cannot be reported as a success or failure. Moreover, task completion, without a

systematic dynamic assessment, cannot be a rational and proper determining factor for

identifying the learner's needs and their required instructions to attain their goals (TETZLAFF,

et al. 2020).

Figure 6. Task performance evaluation in TMM

Source: Author’s archive

The role of need analysis and progress evaluation is even more obvious in intermediate

and pre-advanced levels of language proficiency in that, at these levels, the main focus of

learning is on developing effective communication rather than focusing on linguistic features;

therefore, the role of receiving constructive feedback according to a systematic dynamic

assessment is remarkably obvious which found to be missing in TMM.

Discussion

Personalization in language learning has been emphasized in the literature as an

effective method of instruction (POLLARD; JAMES, 2004; BERNARD, 2005; TOMLINSON,

2013; TETZLAFF et al., 2020) and TMM is one of the learning programs that provides its users

with a personalized learning environment. Although most studies in the literature demonstrated

the learners' positive attitude toward using TMM (e.g., HASHIM; YUNUS; 2010; NIELSON,

2011; EPINOSA, 2013; UTHAYAKUMARAN; KASSIM, 2018) and its effectiveness on

various aspects of language learning (e.g., PEREZ, 2014; AYULISTYA, 2016; GYAMFI;

SUKSEEMUANG, 2017) the personalized learning reliability of this courseware has not been

explored before this study.

Personalized learning reliability is defined in this research as the degree to which two

hypothetical identical learners with the same level of language proficiency and personal

preferences will receive the same level of instruction and learning support from the courseware.

With respect to this definition and the results of data analysis, TMM was found to be not of

high personalized learning reliability due to the lack of two types of assessment: 1) a placement

test at the beginning of the learning procedure; and 2) dynamic assessments throughout the

learning procedure. The results are achieved within the theoretical framework of Tetzlaff et al.

(2020) in which the reliability and effectiveness of a personalized learning program will be

achieved through constant dynamic assessment in which learners' level of proficiency and

educational needs are measured repeatedly throughout the learning procedure.

Conclusion

TMM is a practical and motivating courseware in educational programs; however, in

order to increase the personalized learning reliability of it, TMM should be equipped with a

placement test at the beginning of the learning procedure and a constant dynamic assessment

technology throughout the whole learning process and instruction. Relying on adaptive

activities which are chosen unsystematically by the learners themselves, which is the case with

the current version of the TMM program, is not reliable, since most language learners are

neither capable of professionally estimating their own level of language proficiency at the

beginning of the course nor are they trained to determine the required level of task difficulty

for each lesson and activity throughout the course. The results have implications for courseware

designers to consider placement tests and dynamic assessment technology in their future

designs to maximize the reliability and effectiveness of their personalized learning programs.

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How to reference this article

SHOBEIRY, M. Personalized learning reliability of tell me more: a dynamic approach. Rev.

EntreLínguas, Araraquara, v. 7, n. esp. 4, e021068, Nov 2021. e-ISSN: 2447-3529.

DOI: https://doi.org/10.29051/el.v7iesp.4.15604

Submitted: 09/02/2022

Required revisions: 20/05/2022

Approved: 05/09/2022

Published: 10/11/2022

CONFIABILIDADE DE APRENDIZAGEM PERSONALIZADA DE TELL ME

MORE: UMA ABORDAGEM DINÂMICA

PERSONALIZED LEARNING RELIABILITY OF TELL ME MORE: A DYNAMIC

APPROACH

FIABILIDAD DE APRENDIZAJE PERSONALIZADO DE TELL ME MORE: UN

ENFOQUE DINÁMICO

Maria SHOBEIRY

RESUMO: Este estudo investigou a confiabilidade de aprendizagem personalizada do Tell Me

More (TMM) (ou seja, a extensão em que dois alunos hipotéticos idênticos recebem o mesmo

nível de apoio instrucional e de aprendizagem ao usar um material didático) dentro da estrutura

dinâmica de Tetzlaff, Schmiedek e Brod (2020), em que a aprendizagem personalizada é

considerada a mais confiável e eficaz quando as características dos alunos são avaliados

dinamicamente durante o processo de aprendizagem e as instruções são fornecidas a eles de

acordo. As aulas, workshops e atividades do modo Dinâmico do TMM foram analisadas

qualitativamente e os resultados revelaram que para que o TMM proporcione uma

aprendizagem personalizada confiável, ele deve ser equipado com um teste de nivelamento no

início do curso e uma tecnologia de avaliação dinâmica constante ao longo do processo de